Final_Modelling_BTC_tweets_sentiment_market_effect_LSTM.ipynb

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          "text": [
            "/kaggle/input/bitcoin-price-history/BTC-USD.csv\n",
            "/kaggle/input/bitcoin-tweets/Bitcoin_tweets.csv\n"
          ]
        }
      ],
      "source": [
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)"
      ]
    },
    {
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          "text": [
            "Collecting vaderSentiment\r\n",
            "  Downloading vaderSentiment-3.3.2-py2.py3-none-any.whl (125 kB)\r\n",
            "     |████████████████████████████████| 125 kB 287 kB/s            \r\n",
            "\u001b[?25hRequirement already satisfied: requests in /opt/conda/lib/python3.7/site-packages (from vaderSentiment) (2.26.0)\r\n",
            "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests->vaderSentiment) (3.1)\r\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.7/site-packages (from requests->vaderSentiment) (2021.10.8)\r\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /opt/conda/lib/python3.7/site-packages (from requests->vaderSentiment) (2.0.9)\r\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests->vaderSentiment) (1.26.7)\r\n",
            "Installing collected packages: vaderSentiment\r\n",
            "Successfully installed vaderSentiment-3.3.2\r\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\r\n"
          ]
        }
      ],
      "source": [
        "! pip install vaderSentiment"
      ]
    },
    {
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      "source": [
        "from time import sleep\n",
        "import json\n",
        "import pandas as pd\n",
        "import io\n",
        "import re\n",
        "import numpy as np\n",
        "from tqdm import tqdm\n",
        "import pandas as pd\n",
        "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer\n",
        "from tqdm import tnrange, tqdm_notebook, tqdm\n",
        "\n",
        "from sklearn import preprocessing\n",
        "import matplotlib.pyplot as plt\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "CJDdN5phtWQX"
      },
      "id": "CJDdN5phtWQX",
      "execution_count": null,
      "outputs": []
    },
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      "outputs": [],
      "source": [
        "tweets_raw_file   = '/content/drive/MyDrive/Capstone/Bitcoin_tweets.csv'\n",
        "tweets_clean_file = '/content/drive/MyDrive/Capstone/Bitcoin_tweets_clean.csv'\n",
        "bit_price_file2 = '/content/drive/MyDrive/Capstone/BTC-USD.csv'\n"
      ]
    },
    {
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            "(2259788, 13)\n"
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              "      <th>user_verified</th>\n",
              "      <th>date</th>\n",
              "      <th>text</th>\n",
              "      <th>hashtags</th>\n",
              "      <th>source</th>\n",
              "      <th>is_retweet</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>DeSota Wilson</td>\n",
              "      <td>Atlanta, GA</td>\n",
              "      <td>Biz Consultant, real estate, fintech, startups...</td>\n",
              "      <td>2009-04-26 20:05:09</td>\n",
              "      <td>8534.0</td>\n",
              "      <td>7605</td>\n",
              "      <td>4838</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-02-10 23:59:04</td>\n",
              "      <td>Blue Ridge Bank shares halted by NYSE after #b...</td>\n",
              "      <td>['bitcoin']</td>\n",
              "      <td>Twitter Web App</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CryptoND</td>\n",
              "      <td>NaN</td>\n",
              "      <td>😎 BITCOINLIVE is a Dutch platform aimed at inf...</td>\n",
              "      <td>2019-10-17 20:12:10</td>\n",
              "      <td>6769.0</td>\n",
              "      <td>1532</td>\n",
              "      <td>25483</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-02-10 23:58:48</td>\n",
              "      <td>😎 Today, that's this #Thursday, we will do a \"...</td>\n",
              "      <td>['Thursday', 'Btc', 'wallet', 'security']</td>\n",
              "      <td>Twitter for Android</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Tdlmatias</td>\n",
              "      <td>London, England</td>\n",
              "      <td>IM Academy : The best #forex, #SelfEducation, ...</td>\n",
              "      <td>2014-11-10 10:50:37</td>\n",
              "      <td>128.0</td>\n",
              "      <td>332</td>\n",
              "      <td>924</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-02-10 23:54:48</td>\n",
              "      <td>Guys evening, I have read this article about B...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Twitter Web App</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Crypto is the future</td>\n",
              "      <td>NaN</td>\n",
              "      <td>I will post a lot of buying signals for BTC tr...</td>\n",
              "      <td>2019-09-28 16:48:12</td>\n",
              "      <td>625.0</td>\n",
              "      <td>129</td>\n",
              "      <td>14</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-02-10 23:54:33</td>\n",
              "      <td>$BTC A big chance in a billion! Price: \\487264...</td>\n",
              "      <td>['Bitcoin', 'FX', 'BTC', 'crypto']</td>\n",
              "      <td>dlvr.it</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Alex Kirchmaier 🇦🇹🇸🇪 #FactsSuperspreader</td>\n",
              "      <td>Europa</td>\n",
              "      <td>Co-founder @RENJERJerky | Forbes 30Under30 | I...</td>\n",
              "      <td>2016-02-03 13:15:55</td>\n",
              "      <td>1249.0</td>\n",
              "      <td>1472</td>\n",
              "      <td>10482</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-02-10 23:54:06</td>\n",
              "      <td>This network is secured by 9 508 nodes as of t...</td>\n",
              "      <td>['BTC']</td>\n",
              "      <td>Twitter Web App</td>\n",
              "      <td>False</td>\n",
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            "text/plain": [
              "                                  user_name    user_location  \\\n",
              "0                             DeSota Wilson      Atlanta, GA   \n",
              "1                                  CryptoND              NaN   \n",
              "2                                 Tdlmatias  London, England   \n",
              "3                      Crypto is the future              NaN   \n",
              "4  Alex Kirchmaier 🇦🇹🇸🇪 #FactsSuperspreader           Europa   \n",
              "\n",
              "                                    user_description         user_created  \\\n",
              "0  Biz Consultant, real estate, fintech, startups...  2009-04-26 20:05:09   \n",
              "1  😎 BITCOINLIVE is a Dutch platform aimed at inf...  2019-10-17 20:12:10   \n",
              "2  IM Academy : The best #forex, #SelfEducation, ...  2014-11-10 10:50:37   \n",
              "3  I will post a lot of buying signals for BTC tr...  2019-09-28 16:48:12   \n",
              "4  Co-founder @RENJERJerky | Forbes 30Under30 | I...  2016-02-03 13:15:55   \n",
              "\n",
              "   user_followers user_friends user_favourites user_verified  \\\n",
              "0          8534.0         7605            4838         False   \n",
              "1          6769.0         1532           25483         False   \n",
              "2           128.0          332             924         False   \n",
              "3           625.0          129              14         False   \n",
              "4          1249.0         1472           10482         False   \n",
              "\n",
              "                  date                                               text  \\\n",
              "0  2021-02-10 23:59:04  Blue Ridge Bank shares halted by NYSE after #b...   \n",
              "1  2021-02-10 23:58:48  😎 Today, that's this #Thursday, we will do a \"...   \n",
              "2  2021-02-10 23:54:48  Guys evening, I have read this article about B...   \n",
              "3  2021-02-10 23:54:33  $BTC A big chance in a billion! Price: \\487264...   \n",
              "4  2021-02-10 23:54:06  This network is secured by 9 508 nodes as of t...   \n",
              "\n",
              "                                    hashtags               source is_retweet  \n",
              "0                                ['bitcoin']      Twitter Web App      False  \n",
              "1  ['Thursday', 'Btc', 'wallet', 'security']  Twitter for Android      False  \n",
              "2                                        NaN      Twitter Web App      False  \n",
              "3         ['Bitcoin', 'FX', 'BTC', 'crypto']              dlvr.it      False  \n",
              "4                                    ['BTC']      Twitter Web App      False  "
            ]
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      ],
      "source": [
        "df_raw = pd.read_csv(\"/content/drive/MyDrive/Capstone/tweets_raw_file\")\n",
        "print(df_raw.shape)\n",
        "df_raw.head(5)"
      ]
    },
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          "name": "stderr",
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          "text": [
            "100%|██████████| 22598/22598 [00:48<00:00, 464.29it/s] \n"
          ]
        }
      ],
      "source": [
        "# cleaning dataframe \n",
        "df_raw = df_raw.sort_values(by = 'date')\n",
        "dd = df_raw.sample(frac=0.01, replace=False, random_state=1)\n",
        "dd.reset_index(inplace=True)\n",
        "for i,s in enumerate(tqdm(dd['text'],position=0, leave=True)):\n",
        "    text = str(dd.loc[i, 'text'])\n",
        "    text = text.replace(\"#\", \"\")\n",
        "    text = re.sub('https?://(?:[-\\w.]|(?:%[\\da-fA-F]{2}))+', '', text, flags=re.MULTILINE)\n",
        "    text = re.sub('@\\\\w+ *', '', text, flags=re.MULTILINE)\n",
        "    dd.loc[i, 'text'] = text\n",
        "dd.to_csv(tweets_clean_file, header=True, encoding='utf-8',index=False)"
      ]
    },
    {
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      "source": [
        "## Sentiment anatweets_clean_fileh Vader\n",
        "VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media.\n",
        "\n",
        "VADER takes into account\n",
        "\n",
        "negations and contractions (not good, wasn’t good)\n",
        "Punctuation (good!!!), CAPS, emotes :), emojis\n",
        "Intensificators (very, kind of), acronyms ‘lol’\n",
        "Scores between -1.0 (negative) and 1.0 (positive)\n",
        "\n",
        "We will use this sentiment analysis of the tweets to calculate a score that will represent the importance of each tweet."
      ]
    },
    {
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      "source": [
        "df_clean = pd.read_csv(tweets_clean_file)"
      ]
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            "100%|██████████| 22598/22598 [00:04<00:00, 4745.09it/s]\n"
          ]
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              "      <th>user_favourites</th>\n",
              "      <th>user_verified</th>\n",
              "      <th>date</th>\n",
              "      <th>text</th>\n",
              "      <th>hashtags</th>\n",
              "      <th>source</th>\n",
              "      <th>is_retweet</th>\n",
              "      <th>compound</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>195760</td>\n",
              "      <td>محمد</td>\n",
              "      <td>esfahan</td>\n",
              "      <td>‏‏‏خودت رو به خودت ثابت کن،نه به دیگران</td>\n",
              "      <td>2021-01-02 19:08:56</td>\n",
              "      <td>616.0</td>\n",
              "      <td>1683.0</td>\n",
              "      <td>1712.0</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-06-22 05:22:52</td>\n",
              "      <td>nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...</td>\n",
              "      <td>['ortcoin', 'ort', 'okratech', 'bitcoin', 'air...</td>\n",
              "      <td>Twitter for Android</td>\n",
              "      <td>False</td>\n",
              "      <td>0.5994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1135874</td>\n",
              "      <td>Crypto Revolution Merchandise 💚</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Crypto Revolution the Wave of change 👊😎👊 Not y...</td>\n",
              "      <td>2019-10-13 06:16:05</td>\n",
              "      <td>451.0</td>\n",
              "      <td>2045.0</td>\n",
              "      <td>45077.0</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-08-25 07:06:40</td>\n",
              "      <td>Long Bitcoin short the banks 🧐</td>\n",
              "      <td>['Bitcoin']</td>\n",
              "      <td>Twitter Web App</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     index                        user_name user_location  \\\n",
              "0   195760                             محمد       esfahan   \n",
              "1  1135874  Crypto Revolution Merchandise 💚           NaN   \n",
              "\n",
              "                                    user_description         user_created  \\\n",
              "0            ‏‏‏خودت رو به خودت ثابت کن،نه به دیگران  2021-01-02 19:08:56   \n",
              "1  Crypto Revolution the Wave of change 👊😎👊 Not y...  2019-10-13 06:16:05   \n",
              "\n",
              "   user_followers  user_friends  user_favourites user_verified  \\\n",
              "0           616.0        1683.0           1712.0         False   \n",
              "1           451.0        2045.0          45077.0         False   \n",
              "\n",
              "                  date                                               text  \\\n",
              "0  2021-06-22 05:22:52  nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...   \n",
              "1  2021-08-25 07:06:40                     Long Bitcoin short the banks 🧐   \n",
              "\n",
              "                                            hashtags               source  \\\n",
              "0  ['ortcoin', 'ort', 'okratech', 'bitcoin', 'air...  Twitter for Android   \n",
              "1                                        ['Bitcoin']      Twitter Web App   \n",
              "\n",
              "  is_retweet  compound  \n",
              "0      False    0.5994  \n",
              "1      False    0.0000  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "analyzer = SentimentIntensityAnalyzer()\n",
        "compound = []\n",
        "for i,s in enumerate(tqdm(df_clean['text'],position=0, leave=True)):\n",
        "    vs = analyzer.polarity_scores(str(s))\n",
        "    compound.append(vs[\"compound\"])\n",
        "df_clean[\"compound\"] = compound\n",
        "df_clean.head(2)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "1869f8cf",
      "metadata": {
        "papermill": {
          "duration": 0.209822,
          "end_time": "2022-02-03T01:55:34.823306",
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          "status": "completed"
        },
        "tags": [],
        "id": "1869f8cf"
      },
      "source": [
        "## Calculating score for each tweet\n",
        "To calculate the score for each tweet, I am going to  use different variables for which I have a weight based on importance.\n",
        "\n",
        "The compound column represents the sentiment of the tweets and the values are between -1 and 1.\n",
        "\n",
        "I am using the number of retweets, the number of likes, and the number of users that follow the tweet's author in the formula below."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "386fa563",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:35.255555Z",
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          "status": "completed"
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        "tags": [],
        "id": "386fa563",
        "outputId": "b0ba2ea1-0f7a-4e73-c2c1-5b49f09512d0"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "100%|██████████| 22598/22598 [00:01<00:00, 13184.90it/s]\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>user_name</th>\n",
              "      <th>user_location</th>\n",
              "      <th>user_description</th>\n",
              "      <th>user_created</th>\n",
              "      <th>user_followers</th>\n",
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              "      <th>user_favourites</th>\n",
              "      <th>user_verified</th>\n",
              "      <th>date</th>\n",
              "      <th>text</th>\n",
              "      <th>hashtags</th>\n",
              "      <th>source</th>\n",
              "      <th>is_retweet</th>\n",
              "      <th>compound</th>\n",
              "      <th>score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>195760</td>\n",
              "      <td>محمد</td>\n",
              "      <td>esfahan</td>\n",
              "      <td>‏‏‏خودت رو به خودت ثابت کن،نه به دیگران</td>\n",
              "      <td>2021-01-02 19:08:56</td>\n",
              "      <td>616.0</td>\n",
              "      <td>1683.0</td>\n",
              "      <td>1712.0</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-06-22 05:22:52</td>\n",
              "      <td>nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...</td>\n",
              "      <td>['ortcoin', 'ort', 'okratech', 'bitcoin', 'air...</td>\n",
              "      <td>Twitter for Android</td>\n",
              "      <td>False</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>1025.108064</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1135874</td>\n",
              "      <td>Crypto Revolution Merchandise 💚</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Crypto Revolution the Wave of change 👊😎👊 Not y...</td>\n",
              "      <td>2019-10-13 06:16:05</td>\n",
              "      <td>451.0</td>\n",
              "      <td>2045.0</td>\n",
              "      <td>45077.0</td>\n",
              "      <td>False</td>\n",
              "      <td>2021-08-25 07:06:40</td>\n",
              "      <td>Long Bitcoin short the banks 🧐</td>\n",
              "      <td>['Bitcoin']</td>\n",
              "      <td>Twitter Web App</td>\n",
              "      <td>False</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     index                        user_name user_location  \\\n",
              "0   195760                             محمد       esfahan   \n",
              "1  1135874  Crypto Revolution Merchandise 💚           NaN   \n",
              "\n",
              "                                    user_description         user_created  \\\n",
              "0            ‏‏‏خودت رو به خودت ثابت کن،نه به دیگران  2021-01-02 19:08:56   \n",
              "1  Crypto Revolution the Wave of change 👊😎👊 Not y...  2019-10-13 06:16:05   \n",
              "\n",
              "   user_followers  user_friends  user_favourites user_verified  \\\n",
              "0           616.0        1683.0           1712.0         False   \n",
              "1           451.0        2045.0          45077.0         False   \n",
              "\n",
              "                  date                                               text  \\\n",
              "0  2021-06-22 05:22:52  nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...   \n",
              "1  2021-08-25 07:06:40                     Long Bitcoin short the banks 🧐   \n",
              "\n",
              "                                            hashtags               source  \\\n",
              "0  ['ortcoin', 'ort', 'okratech', 'bitcoin', 'air...  Twitter for Android   \n",
              "1                                        ['Bitcoin']      Twitter Web App   \n",
              "\n",
              "  is_retweet  compound        score  \n",
              "0      False    0.5994  1025.108064  \n",
              "1      False    0.0000     0.000000  "
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "scores = []\n",
        "for i, s in tqdm(df_clean.iterrows(), total=df_clean.shape[0],position=0, leave=True):\n",
        "    try:\n",
        "        scores.append(s[\"compound\"] * ((int(s[\"user_followers\"]))) * ((int(s[\"user_favourites\"])+1)/int(s['user_followers']+1)) *((int(s[\"is_retweet\"])+1)))\n",
        "    except:\n",
        "        scores.append(np.nan)\n",
        "df_clean[\"score\"] = scores\n",
        "df_clean.head(2)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "c6332300",
      "metadata": {
        "papermill": {
          "duration": 0.225108,
          "end_time": "2022-02-03T01:55:37.449184",
          "exception": false,
          "start_time": "2022-02-03T01:55:37.224076",
          "status": "completed"
        },
        "tags": [],
        "id": "c6332300"
      },
      "source": [
        "## Nexr, Let's read the Bitcoin price "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d0ac329e",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:37.896265Z",
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          "shell.execute_reply.started": "2022-02-03T01:16:32.984271Z"
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          "status": "completed"
        },
        "tags": [],
        "id": "d0ac329e",
        "outputId": "764b0b96-b494-48cb-fdad-20523bc55df2"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2014-09-17</td>\n",
              "      <td>465.864014</td>\n",
              "      <td>468.174011</td>\n",
              "      <td>452.421997</td>\n",
              "      <td>457.334015</td>\n",
              "      <td>457.334015</td>\n",
              "      <td>21056800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2014-09-18</td>\n",
              "      <td>456.859985</td>\n",
              "      <td>456.859985</td>\n",
              "      <td>413.104004</td>\n",
              "      <td>424.440002</td>\n",
              "      <td>424.440002</td>\n",
              "      <td>34483200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Date        Open        High         Low       Close   Adj Close  \\\n",
              "0 2014-09-17  465.864014  468.174011  452.421997  457.334015  457.334015   \n",
              "1 2014-09-18  456.859985  456.859985  413.104004  424.440002  424.440002   \n",
              "\n",
              "     Volume  \n",
              "0  21056800  \n",
              "1  34483200  "
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df_price = pd.read_csv(bit_price_file2)\n",
        "df_price.Date = pd.to_datetime(df_price.Date)\n",
        "df_price.head(2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "655f7ec9",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:38.376632Z",
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          "shell.execute_reply.started": "2022-02-03T01:16:33.009817Z"
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      "outputs": [],
      "source": [
        "# Performing sentiment analysis for final modeling \n",
        "df_clean = df_clean.drop_duplicates()\n",
        "tweets = df_clean.copy()\n",
        "tweets['date'] = pd.to_datetime(tweets['date'],utc=True)\n",
        "tweets.date = tweets.date.dt.tz_localize(None)\n",
        "tweets.index = tweets['date']\n",
        "\n",
        "tweets_grouped = tweets.resample('1h').sum()\n",
        "\n",
        "crypto_usd = df_price.copy()\n",
        "crypto_usd['Date'] = pd.to_datetime(crypto_usd['Date'], unit='s')\n",
        "crypto_usd.index = crypto_usd['Date']\n",
        "\n",
        "crypto_usd_grouped = crypto_usd.resample('D')['Close'].mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a8b7cebe",
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      "outputs": [],
      "source": [
        "def crosscorr(datax, datay, lag=0, method=\"pearson\"):\n",
        "    \"\"\" Lag-N cross correlation. \n",
        "    Parameters\n",
        "    —------—\n",
        "    lag : int, default 0\n",
        "    datax, datay : pandas.Series objects of equal length\n",
        "\n",
        "    Returns\n",
        "    —------—\n",
        "    crosscorr : float\n",
        "    \"\"\"\n",
        "    return datax.corrwith(datay.shift(lag), method=method)['score']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "0411412b",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:39.425444Z",
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          "shell.execute_reply.started": "2022-02-03T01:16:33.124818Z"
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        "id": "0411412b"
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      "outputs": [],
      "source": [
        "beggining = max(tweets_grouped.index.min().replace(tzinfo=None), crypto_usd_grouped.index.min())\n",
        "end = min(tweets_grouped.index.max().replace(tzinfo=None), crypto_usd_grouped.index.max())\n",
        "tweets_grouped = tweets_grouped[beggining:end]\n",
        "crypto_usd_grouped = crypto_usd_grouped[beggining:end]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b092818e",
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      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, ax1 = plt.subplots(figsize=(20,10))\n",
        "ax1.set_title(\"Crypto currency evolution compared to twitter sentiment\", fontsize=18)\n",
        "ax1.tick_params(labelsize=14)\n",
        "ax2 = ax1.twinx()\n",
        "ax1.plot_date(tweets_grouped.index, tweets_grouped, 'g-')\n",
        "ax2.plot_date(crypto_usd_grouped.index, crypto_usd_grouped, 'b-')\n",
        "\n",
        "ax1.set_ylabel(\"Sentiment\", color='g', fontsize=16)\n",
        "ax2.set_ylabel(\"Bitcoin [$]\", color='b', fontsize=16)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b44c939a",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:40.800948Z",
          "iopub.status.busy": "2022-02-03T01:55:40.799924Z",
          "iopub.status.idle": "2022-02-03T01:55:42.306294Z",
          "shell.execute_reply": "2022-02-03T01:55:42.305036Z",
          "shell.execute_reply.started": "2022-02-03T01:16:35.714673Z"
        },
        "papermill": {
          "duration": 1.734549,
          "end_time": "2022-02-03T01:55:42.306467",
          "exception": false,
          "start_time": "2022-02-03T01:55:40.571918",
          "status": "completed"
        },
        "tags": [],
        "id": "b44c939a",
        "outputId": "9bb4e076-cdfc-4a79-f943-e08ba78d29fe"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "xcov = [crosscorr(tweets_grouped, crypto_usd_grouped, lag=i, method=\"pearson\") for i in range(-20,20)]\n",
        "plt.plot(range(-20,20), xcov)\n",
        "plt.title(\"pearson cross-correlation\")\n",
        "plt.xlabel(\"lag\")\n",
        "plt.ylabel(\"correlation\")\n",
        "plt.show()\n",
        "\n",
        "xcov = [crosscorr(tweets_grouped, crypto_usd_grouped, lag=i, method=\"kendall\") for i in range(-20,20)]\n",
        "plt.plot(range(-20,20), xcov)\n",
        "plt.title(\"kendall cross-correlation\")\n",
        "plt.xlabel(\"lag\")\n",
        "plt.ylabel(\"correlation\")\n",
        "plt.show()\n",
        "\n",
        "xcov = [crosscorr(tweets_grouped, crypto_usd_grouped, lag=i, method=\"spearman\") for i in range(-20,20)]\n",
        "plt.plot(range(-20,20), xcov)\n",
        "plt.title(\"spearman cross-correlation\")\n",
        "plt.xlabel(\"lag\")\n",
        "plt.ylabel(\"correlation\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "d8d303a8",
      "metadata": {
        "papermill": {
          "duration": 0.229664,
          "end_time": "2022-02-03T01:55:42.762414",
          "exception": false,
          "start_time": "2022-02-03T01:55:42.532750",
          "status": "completed"
        },
        "tags": [],
        "id": "d8d303a8"
      },
      "source": [
        "## Normalization"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "17ef63b2",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:43.214229Z",
          "iopub.status.busy": "2022-02-03T01:55:43.213449Z",
          "iopub.status.idle": "2022-02-03T01:55:43.584167Z",
          "shell.execute_reply": "2022-02-03T01:55:43.584683Z",
          "shell.execute_reply.started": "2022-02-03T01:16:37.170358Z"
        },
        "papermill": {
          "duration": 0.598206,
          "end_time": "2022-02-03T01:55:43.584874",
          "exception": false,
          "start_time": "2022-02-03T01:55:42.986668",
          "status": "completed"
        },
        "tags": [],
        "id": "17ef63b2",
        "outputId": "84279d3f-2f78-4f87-935c-d29a9d5cc533"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Normalizing time series data\n",
        "min_max_scaler = preprocessing.StandardScaler()\n",
        "score_scaled = min_max_scaler.fit_transform(tweets_grouped['score'].values.reshape(-1,1))\n",
        "tweets_grouped['normalized_score'] = score_scaled\n",
        "crypto_used_grouped_scaled = crypto_usd_grouped / max(crypto_usd_grouped.max(), abs(crypto_usd_grouped.min()))\n",
        "\n",
        "fig, ax1 = plt.subplots(figsize=(20,10))\n",
        "ax1.set_title(\"Normalized Crypto currency evolution compared to normalized twitter sentiment\", fontsize=18)\n",
        "ax1.tick_params(labelsize=14)\n",
        "\n",
        "ax2 = ax1.twinx()\n",
        "ax1.plot_date(tweets_grouped.index, tweets_grouped['normalized_score'], 'g-')\n",
        "ax2.plot_date(crypto_usd_grouped.index, crypto_used_grouped_scaled, 'b-')\n",
        "\n",
        "ax1.set_ylabel(\"Sentiment\", color='g', fontsize=16)\n",
        "ax2.set_ylabel(\"Bitcoin normalized\", color='b', fontsize=16)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b94881fa",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:44.047406Z",
          "iopub.status.busy": "2022-02-03T01:55:44.046639Z",
          "iopub.status.idle": "2022-02-03T01:55:44.505223Z",
          "shell.execute_reply": "2022-02-03T01:55:44.505717Z",
          "shell.execute_reply.started": "2022-02-03T01:16:39.291595Z"
        },
        "papermill": {
          "duration": 0.695384,
          "end_time": "2022-02-03T01:55:44.505947",
          "exception": false,
          "start_time": "2022-02-03T01:55:43.810563",
          "status": "completed"
        },
        "tags": [],
        "id": "b94881fa",
        "outputId": "4d3efc76-97a2-432e-9326-dc5f0e95973c"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "xcov = [crosscorr(tweets_grouped, crypto_usd_grouped, lag=i) for i in range(-20,20)]\n",
        "plt.plot(range(-20,20), xcov)\n",
        "plt.title(\"lag's impact on correlation (normalized)\")\n",
        "plt.xlabel(\"lag\")\n",
        "plt.ylabel(\"correlation\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "504946e9",
      "metadata": {
        "papermill": {
          "duration": 0.233423,
          "end_time": "2022-02-03T01:55:44.980396",
          "exception": false,
          "start_time": "2022-02-03T01:55:44.746973",
          "status": "completed"
        },
        "tags": [],
        "id": "504946e9"
      },
      "source": [
        "## Derivatives of BTC price "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4089be65",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:45.453437Z",
          "iopub.status.busy": "2022-02-03T01:55:45.452680Z",
          "iopub.status.idle": "2022-02-03T01:55:45.458913Z",
          "shell.execute_reply": "2022-02-03T01:55:45.459478Z",
          "shell.execute_reply.started": "2022-02-03T01:16:44.465605Z"
        },
        "papermill": {
          "duration": 0.244943,
          "end_time": "2022-02-03T01:55:45.459665",
          "exception": false,
          "start_time": "2022-02-03T01:55:45.214722",
          "status": "completed"
        },
        "tags": [],
        "id": "4089be65"
      },
      "outputs": [],
      "source": [
        "# Derivatives\n",
        "tweets_grouped_derivative = pd.Series(np.gradient(tweets_grouped['normalized_score'].values), tweets_grouped.index, name='slope')\n",
        "crypto_usd_grouped_derivative = pd.Series(np.gradient(crypto_usd_grouped.values), crypto_usd_grouped.index, name='slope')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "1debc368",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:45.937547Z",
          "iopub.status.busy": "2022-02-03T01:55:45.936225Z",
          "iopub.status.idle": "2022-02-03T01:55:46.344689Z",
          "shell.execute_reply": "2022-02-03T01:55:46.345224Z",
          "shell.execute_reply.started": "2022-02-03T01:16:45.600865Z"
        },
        "papermill": {
          "duration": 0.648148,
          "end_time": "2022-02-03T01:55:46.345412",
          "exception": false,
          "start_time": "2022-02-03T01:55:45.697264",
          "status": "completed"
        },
        "tags": [],
        "id": "1debc368",
        "outputId": "d64c0710-a35b-4060-f6f9-c9694b16b28c"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, ax1 = plt.subplots(figsize=(20,10))\n",
        "ax1.set_title(\"Derivative of crypto currency and sentiment's score\", fontsize=18)\n",
        "ax1.tick_params(labelsize=14)\n",
        "\n",
        "ax2 = ax1.twinx()\n",
        "ax1.plot_date(tweets_grouped_derivative.index, tweets_grouped_derivative, 'g-')\n",
        "ax2.plot_date(crypto_usd_grouped_derivative.index, crypto_usd_grouped_derivative, 'b-')\n",
        "\n",
        "ax1.set_ylabel(\"Sentiment's derivative\", color='g', fontsize=16)\n",
        "ax2.set_ylabel('Bitcoin price derivative', color='b', fontsize=16)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9b1ce386",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:55:46.826962Z",
          "iopub.status.busy": "2022-02-03T01:55:46.825914Z",
          "iopub.status.idle": "2022-02-03T01:55:48.644310Z",
          "shell.execute_reply": "2022-02-03T01:55:48.643317Z",
          "shell.execute_reply.started": "2022-02-03T01:16:46.479818Z"
        },
        "papermill": {
          "duration": 2.06293,
          "end_time": "2022-02-03T01:55:48.644468",
          "exception": false,
          "start_time": "2022-02-03T01:55:46.581538",
          "status": "completed"
        },
        "tags": [],
        "id": "9b1ce386",
        "outputId": "435492d6-a297-4743-ba3f-fe5dd76103f4"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "xcov = [crosscorr(tweets_grouped, crypto_usd_grouped_derivative, lag=i, method=\"pearson\") for i in range(-20,20)]\n",
        "plt.plot(range(-20,20), xcov)\n",
        "plt.title(\"pearson cross-corelation (derivative)\")\n",
        "plt.xlabel(\"lag\")\n",
        "plt.ylabel(\"correlation\")\n",
        "plt.show()\n",
        "\n",
        "xcov = [crosscorr(tweets_grouped, crypto_usd_grouped_derivative, lag=i, method=\"kendall\") for i in range(-20,20)]\n",
        "plt.plot(range(-20,20), xcov)\n",
        "plt.title(\"kendall cross-corelation (derivative)\")\n",
        "plt.xlabel(\"lag\")\n",
        "plt.ylabel(\"correlation\")\n",
        "plt.show()\n",
        "\n",
        "xcov = [crosscorr(tweets_grouped, crypto_usd_grouped_derivative, lag=i, method=\"spearman\") for i in range(-20,20)]\n",
        "plt.plot(range(-20,20), xcov)\n",
        "plt.title(\"spearman cross-corelation (derivative)\")\n",
        "plt.xlabel(\"lag\")\n",
        "plt.ylabel(\"correlation\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "960e8d95",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-01-30T00:57:23.278911Z",
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          "shell.execute_reply": "2022-01-30T00:57:23.282262Z",
          "shell.execute_reply.started": "2022-01-30T00:57:23.278882Z"
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          "status": "completed"
        },
        "tags": [],
        "id": "960e8d95"
      },
      "source": [
        "# Part 2 NLP Modeling to clean the data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5e39f4e8",
      "metadata": {
        "execution": {
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          "status": "completed"
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        "tags": [],
        "id": "5e39f4e8",
        "outputId": "9137be2a-69a3-4447-e9df-47d76bbad7de"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: textblob in /opt/conda/lib/python3.7/site-packages (0.17.1)\r\n",
            "Requirement already satisfied: nltk>=3.1 in /opt/conda/lib/python3.7/site-packages (from textblob) (3.2.4)\r\n",
            "Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from nltk>=3.1->textblob) (1.16.0)\r\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\r\n"
          ]
        },
        {
          "data": {
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              "<div>\n",
              "<style scoped>\n",
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              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tweets</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Long Bitcoin short the banks 🧐</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Top Trending Cryptocurrency Post - DOGECOIN Se...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Can one expect another wave of BTC's decline s...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>We will see…\\n\\nbitcoin btc bnb band bake $btc...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                              tweets\n",
              "0  nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...\n",
              "1                     Long Bitcoin short the banks 🧐\n",
              "2  Top Trending Cryptocurrency Post - DOGECOIN Se...\n",
              "3  Can one expect another wave of BTC's decline s...\n",
              "4  We will see…\\n\\nbitcoin btc bnb band bake $btc..."
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "! pip install textblob \n",
        "from textblob import TextBlob\n",
        "\n",
        "df = df_clean.copy()\n",
        "df.dropna(subset=['hashtags'], inplace=True)\n",
        "df = df[['text']] \n",
        "df.columns = ['tweets']\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d15a96f4",
      "metadata": {
        "execution": {
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        },
        "tags": [],
        "id": "d15a96f4",
        "outputId": "d1f11368-3289-4c07-df44-ced7f1413ed5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package wordnet to /usr/share/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /usr/share/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /usr/share/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n"
          ]
        }
      ],
      "source": [
        "import nltk\n",
        "from nltk.stem.wordnet import WordNetLemmatizer\n",
        "\n",
        "nltk.download('wordnet')\n",
        "nltk.download('stopwords')\n",
        "nltk.download('punkt')\n",
        "stop_words = nltk.corpus.stopwords.words(['english'])\n",
        "\n",
        "print(stop_words)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ac4fe094",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:01.001220Z",
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          "status": "completed"
        },
        "tags": [],
        "id": "ac4fe094"
      },
      "outputs": [],
      "source": [
        "from nltk.tokenize import TweetTokenizer\n",
        "from nltk.stem.wordnet import WordNetLemmatizer\n",
        "lem = WordNetLemmatizer()\n",
        "\n",
        "def cleaning(data):\n",
        "    #removing urls\n",
        "    tweet_without_url = re.sub(r'http\\S+',' ', data)\n",
        "\n",
        "    #removing hashtags\n",
        "    tweet_without_hashtag = re.sub(r'#\\w+', ' ', tweet_without_url)\n",
        "\n",
        "    #3. Removing mentions and characters that not in the English alphabets\n",
        "    tweet_without_mentions = re.sub(r'@\\w+',' ', tweet_without_hashtag)\n",
        "    precleaned_tweet = re.sub('[^A-Za-z]+', ' ', tweet_without_mentions)\n",
        "\n",
        "    #2. Tokenizing\n",
        "    tweet_tokens = TweetTokenizer().tokenize(precleaned_tweet)\n",
        "\n",
        "    #3. Removing Puncs\n",
        "    tokens_without_punc = [w for w in tweet_tokens if w.isalpha()]\n",
        "\n",
        "    #4. Removing Stopwords\n",
        "    tokens_without_sw = [t for t in tokens_without_punc if t not in stop_words]\n",
        "\n",
        "    #5. lemmatization\n",
        "    text_cleaned = [lem.lemmatize(t) for t in tokens_without_sw]\n",
        "\n",
        "    #6. Joining the clean data\n",
        "    return \" \".join(text_cleaned)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "28afe393",
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        "execution": {
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          "status": "completed"
        },
        "tags": [],
        "id": "28afe393",
        "outputId": "6c8c6580-59cd-4901-9c3e-1028e59358bb"
      },
      "outputs": [
        {
          "data": {
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              "\n",
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              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tweets</th>\n",
              "      <th>cleaned_tweets</th>\n",
              "      <th>date_clean</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...</td>\n",
              "      <td>nice project ortcoin ort okratech bitcoin aird...</td>\n",
              "      <td>2021-06-22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Long Bitcoin short the banks 🧐</td>\n",
              "      <td>Long Bitcoin short bank</td>\n",
              "      <td>2021-08-25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Top Trending Cryptocurrency Post - DOGECOIN Se...</td>\n",
              "      <td>Top Trending Cryptocurrency Post DOGECOIN Sell...</td>\n",
              "      <td>2021-07-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Can one expect another wave of BTC's decline s...</td>\n",
              "      <td>Can one expect another wave BTC decline soon v...</td>\n",
              "      <td>2021-07-24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>We will see…\\n\\nbitcoin btc bnb band bake $btc...</td>\n",
              "      <td>We see bitcoin btc bnb band bake btc dCc xZ dP</td>\n",
              "      <td>2021-05-29</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                              tweets  \\\n",
              "0  nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...   \n",
              "1                     Long Bitcoin short the banks 🧐   \n",
              "2  Top Trending Cryptocurrency Post - DOGECOIN Se...   \n",
              "3  Can one expect another wave of BTC's decline s...   \n",
              "4  We will see…\\n\\nbitcoin btc bnb band bake $btc...   \n",
              "\n",
              "                                      cleaned_tweets  date_clean  \n",
              "0  nice project ortcoin ort okratech bitcoin aird...  2021-06-22  \n",
              "1                            Long Bitcoin short bank  2021-08-25  \n",
              "2  Top Trending Cryptocurrency Post DOGECOIN Sell...  2021-07-02  \n",
              "3  Can one expect another wave BTC decline soon v...  2021-07-24  \n",
              "4     We see bitcoin btc bnb band bake btc dCc xZ dP  2021-05-29  "
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df['cleaned_tweets'] = df['tweets'].apply(cleaning)\n",
        "df['date'] = df_clean['date']\n",
        "df['date_clean'] = pd.to_datetime(df['date']).dt.strftime('%Y-%m-%d')\n",
        "df.drop(columns='date',inplace=True)\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "1d94c40d",
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          "status": "completed"
        },
        "tags": [],
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      "outputs": [],
      "source": [
        "def getSubjectivity(tweet):\n",
        "    return TextBlob(tweet).sentiment.subjectivity\n",
        "\n",
        "def getPolarity(tweet):\n",
        "    return TextBlob(tweet).sentiment.polarity"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b52334c5",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:12.494987Z",
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        },
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      "source": [
        "def crypto_price_cate(score):\n",
        "    if score < 1:\n",
        "        return 'negative'\n",
        "    elif score == 1:\n",
        "        return 'neutral'\n",
        "    else:\n",
        "        return 'positive'\n",
        "def observe_period(period):\n",
        "    res = crypto_usd_grouped.shift(period)/crypto_usd_grouped\n",
        "    res = res.apply(crypto_price_cate)\n",
        "    return res \n",
        "\n",
        "time_sentiment = observe_period(7) # compare price ratio in 7 days. price_7_days_later/ price_now \n",
        "df['crypto_sentiment'] = df.date_clean.apply(lambda x: time_sentiment[x] if x in time_sentiment else np.nan)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d39bab00",
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      "outputs": [
        {
          "data": {
            "text/html": [
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              "\n",
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              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tweets</th>\n",
              "      <th>cleaned_tweets</th>\n",
              "      <th>date_clean</th>\n",
              "      <th>crypto_sentiment</th>\n",
              "      <th>subjectivity</th>\n",
              "      <th>polarity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...</td>\n",
              "      <td>nice project ortcoin ort okratech bitcoin aird...</td>\n",
              "      <td>2021-06-22</td>\n",
              "      <td>positive</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Long Bitcoin short the banks 🧐</td>\n",
              "      <td>Long Bitcoin short bank</td>\n",
              "      <td>2021-08-25</td>\n",
              "      <td>negative</td>\n",
              "      <td>0.35</td>\n",
              "      <td>-0.025</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Top Trending Cryptocurrency Post - DOGECOIN Se...</td>\n",
              "      <td>Top Trending Cryptocurrency Post DOGECOIN Sell...</td>\n",
              "      <td>2021-07-02</td>\n",
              "      <td>negative</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Can one expect another wave of BTC's decline s...</td>\n",
              "      <td>Can one expect another wave BTC decline soon v...</td>\n",
              "      <td>2021-07-24</td>\n",
              "      <td>negative</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>We will see…\\n\\nbitcoin btc bnb band bake $btc...</td>\n",
              "      <td>We see bitcoin btc bnb band bake btc dCc xZ dP</td>\n",
              "      <td>2021-05-29</td>\n",
              "      <td>positive</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                              tweets  \\\n",
              "0  nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...   \n",
              "1                     Long Bitcoin short the banks 🧐   \n",
              "2  Top Trending Cryptocurrency Post - DOGECOIN Se...   \n",
              "3  Can one expect another wave of BTC's decline s...   \n",
              "4  We will see…\\n\\nbitcoin btc bnb band bake $btc...   \n",
              "\n",
              "                                      cleaned_tweets  date_clean  \\\n",
              "0  nice project ortcoin ort okratech bitcoin aird...  2021-06-22   \n",
              "1                            Long Bitcoin short bank  2021-08-25   \n",
              "2  Top Trending Cryptocurrency Post DOGECOIN Sell...  2021-07-02   \n",
              "3  Can one expect another wave BTC decline soon v...  2021-07-24   \n",
              "4     We see bitcoin btc bnb band bake btc dCc xZ dP  2021-05-29   \n",
              "\n",
              "  crypto_sentiment  subjectivity  polarity  \n",
              "0         positive          1.00     0.600  \n",
              "1         negative          0.35    -0.025  \n",
              "2         negative          0.40     0.250  \n",
              "3         negative          0.00     0.000  \n",
              "4         positive          0.00     0.000  "
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# may takes time \n",
        "df['subjectivity'] = df['cleaned_tweets'].apply(getSubjectivity)\n",
        "df['polarity'] = df['cleaned_tweets'].apply(getPolarity)\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "cc51d85a",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:30.247664Z",
          "iopub.status.busy": "2022-02-03T01:56:30.246961Z",
          "iopub.status.idle": "2022-02-03T01:56:30.680805Z",
          "shell.execute_reply": "2022-02-03T01:56:30.680185Z",
          "shell.execute_reply.started": "2022-02-03T01:31:56.684412Z"
        },
        "papermill": {
          "duration": 0.690259,
          "end_time": "2022-02-03T01:56:30.680963",
          "exception": false,
          "start_time": "2022-02-03T01:56:29.990704",
          "status": "completed"
        },
        "tags": [],
        "id": "cc51d85a"
      },
      "outputs": [],
      "source": [
        "def getSentiment(score):\n",
        "    if score < 0:\n",
        "        return 'negative'\n",
        "    elif score == 0:\n",
        "        return 'neutral'\n",
        "    else:\n",
        "        return 'positive'\n",
        "df['sentiment'] = df['polarity'].apply(getSentiment)\n",
        "df['target'] = df['sentiment'] == df['crypto_sentiment']\n",
        "df.head()\n",
        "df.to_csv('./df_data.csv')"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "5ed8ef44",
      "metadata": {
        "papermill": {
          "duration": 0.243609,
          "end_time": "2022-02-03T01:56:31.172276",
          "exception": false,
          "start_time": "2022-02-03T01:56:30.928667",
          "status": "completed"
        },
        "tags": [],
        "id": "5ed8ef44"
      },
      "source": [
        "## Model preparation "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "e33e72a8",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:31.666151Z",
          "iopub.status.busy": "2022-02-03T01:56:31.665366Z",
          "iopub.status.idle": "2022-02-03T01:56:38.511378Z",
          "shell.execute_reply": "2022-02-03T01:56:38.510813Z",
          "shell.execute_reply.started": "2022-02-03T01:33:17.048306Z"
        },
        "papermill": {
          "duration": 7.093231,
          "end_time": "2022-02-03T01:56:38.511534",
          "exception": false,
          "start_time": "2022-02-03T01:56:31.418303",
          "status": "completed"
        },
        "tags": [],
        "id": "e33e72a8"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow.keras.preprocessing.text import Tokenizer\n",
        "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
        "import tensorflow.keras.layers as Layers\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.losses import SparseCategoricalCrossentropy\n",
        "from tensorflow.keras.optimizers import Adam\n",
        "from tensorflow.keras.layers import Dense, Dropout, Embedding, LSTM, Conv1D, GlobalMaxPooling1D, Bidirectional, SpatialDropout1D\n",
        "from tensorflow.keras.models import load_model\n",
        "\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from sklearn.metrics import classification_report"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f6644f01",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:39.028398Z",
          "iopub.status.busy": "2022-02-03T01:56:39.027574Z",
          "iopub.status.idle": "2022-02-03T01:56:39.031027Z",
          "shell.execute_reply": "2022-02-03T01:56:39.031510Z",
          "shell.execute_reply.started": "2022-02-03T01:33:18.487660Z"
        },
        "papermill": {
          "duration": 0.271344,
          "end_time": "2022-02-03T01:56:39.031682",
          "exception": false,
          "start_time": "2022-02-03T01:56:38.760338",
          "status": "completed"
        },
        "tags": [],
        "id": "f6644f01",
        "outputId": "5e9139f4-b1cd-4723-c502-dfec43919c51"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tweets</th>\n",
              "      <th>cleaned_tweets</th>\n",
              "      <th>date_clean</th>\n",
              "      <th>crypto_sentiment</th>\n",
              "      <th>subjectivity</th>\n",
              "      <th>polarity</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...</td>\n",
              "      <td>nice project ortcoin ort okratech bitcoin aird...</td>\n",
              "      <td>2021-06-22</td>\n",
              "      <td>positive</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.600</td>\n",
              "      <td>positive</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Long Bitcoin short the banks 🧐</td>\n",
              "      <td>Long Bitcoin short bank</td>\n",
              "      <td>2021-08-25</td>\n",
              "      <td>negative</td>\n",
              "      <td>0.35</td>\n",
              "      <td>-0.025</td>\n",
              "      <td>negative</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Top Trending Cryptocurrency Post - DOGECOIN Se...</td>\n",
              "      <td>Top Trending Cryptocurrency Post DOGECOIN Sell...</td>\n",
              "      <td>2021-07-02</td>\n",
              "      <td>negative</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.250</td>\n",
              "      <td>positive</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Can one expect another wave of BTC's decline s...</td>\n",
              "      <td>Can one expect another wave BTC decline soon v...</td>\n",
              "      <td>2021-07-24</td>\n",
              "      <td>negative</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000</td>\n",
              "      <td>neutral</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>We will see…\\n\\nbitcoin btc bnb band bake $btc...</td>\n",
              "      <td>We see bitcoin btc bnb band bake btc dCc xZ dP</td>\n",
              "      <td>2021-05-29</td>\n",
              "      <td>positive</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000</td>\n",
              "      <td>neutral</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                              tweets  \\\n",
              "0  nice project \\n\\n\\n\\n\\n\\nortcoin ort okratech ...   \n",
              "1                     Long Bitcoin short the banks 🧐   \n",
              "2  Top Trending Cryptocurrency Post - DOGECOIN Se...   \n",
              "3  Can one expect another wave of BTC's decline s...   \n",
              "4  We will see…\\n\\nbitcoin btc bnb band bake $btc...   \n",
              "\n",
              "                                      cleaned_tweets  date_clean  \\\n",
              "0  nice project ortcoin ort okratech bitcoin aird...  2021-06-22   \n",
              "1                            Long Bitcoin short bank  2021-08-25   \n",
              "2  Top Trending Cryptocurrency Post DOGECOIN Sell...  2021-07-02   \n",
              "3  Can one expect another wave BTC decline soon v...  2021-07-24   \n",
              "4     We see bitcoin btc bnb band bake btc dCc xZ dP  2021-05-29   \n",
              "\n",
              "  crypto_sentiment  subjectivity  polarity sentiment  target  \n",
              "0         positive          1.00     0.600  positive    True  \n",
              "1         negative          0.35    -0.025  negative    True  \n",
              "2         negative          0.40     0.250  positive   False  \n",
              "3         negative          0.00     0.000   neutral   False  \n",
              "4         positive          0.00     0.000   neutral   False  "
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ca7a6d20",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:39.527304Z",
          "iopub.status.busy": "2022-02-03T01:56:39.526286Z",
          "iopub.status.idle": "2022-02-03T01:56:39.538812Z",
          "shell.execute_reply": "2022-02-03T01:56:39.539347Z",
          "shell.execute_reply.started": "2022-02-03T01:33:31.743447Z"
        },
        "papermill": {
          "duration": 0.261893,
          "end_time": "2022-02-03T01:56:39.539524",
          "exception": false,
          "start_time": "2022-02-03T01:56:39.277631",
          "status": "completed"
        },
        "tags": [],
        "id": "ca7a6d20"
      },
      "outputs": [],
      "source": [
        "X = df['cleaned_tweets']\n",
        "y = pd.get_dummies(df['sentiment']).values\n",
        "num_classes = df['sentiment'].nunique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f067c046",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:40.038112Z",
          "iopub.status.busy": "2022-02-03T01:56:40.037381Z",
          "iopub.status.idle": "2022-02-03T01:56:40.237712Z",
          "shell.execute_reply": "2022-02-03T01:56:40.236941Z",
          "shell.execute_reply.started": "2022-02-03T01:33:34.527911Z"
        },
        "papermill": {
          "duration": 0.45028,
          "end_time": "2022-02-03T01:56:40.237931",
          "exception": false,
          "start_time": "2022-02-03T01:56:39.787651",
          "status": "completed"
        },
        "tags": [],
        "id": "f067c046",
        "outputId": "994ca028-5364-4d63-d7ca-28508451a35c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(17936,) (4484,) (17936, 3) (4484, 3)\n"
          ]
        }
      ],
      "source": [
        "seed = 38 # fix random seed for reproducibility\n",
        "np.random.seed(seed)\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, \n",
        "                                                    test_size=0.2,\n",
        "                                                    stratify=y,\n",
        "                                                    random_state=seed)\n",
        "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "0fe79160",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:40.742553Z",
          "iopub.status.busy": "2022-02-03T01:56:40.741681Z",
          "iopub.status.idle": "2022-02-03T01:56:41.693965Z",
          "shell.execute_reply": "2022-02-03T01:56:41.694544Z",
          "shell.execute_reply.started": "2022-02-03T01:33:37.267213Z"
        },
        "papermill": {
          "duration": 1.208676,
          "end_time": "2022-02-03T01:56:41.694798",
          "exception": false,
          "start_time": "2022-02-03T01:56:40.486122",
          "status": "completed"
        },
        "tags": [],
        "id": "0fe79160"
      },
      "outputs": [],
      "source": [
        "max_features = 20000\n",
        "tokenizer = Tokenizer(num_words=max_features)\n",
        "tokenizer.fit_on_texts(list(X_train))\n",
        "X_train = tokenizer.texts_to_sequences(X_train)\n",
        "X_test = tokenizer.texts_to_sequences(X_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "88aaadfb",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:42.188074Z",
          "iopub.status.busy": "2022-02-03T01:56:42.187313Z",
          "iopub.status.idle": "2022-02-03T01:56:42.332062Z",
          "shell.execute_reply": "2022-02-03T01:56:42.332971Z",
          "shell.execute_reply.started": "2022-02-03T01:33:38.208314Z"
        },
        "papermill": {
          "duration": 0.395605,
          "end_time": "2022-02-03T01:56:42.333189",
          "exception": false,
          "start_time": "2022-02-03T01:56:41.937584",
          "status": "completed"
        },
        "tags": [],
        "id": "88aaadfb",
        "outputId": "6b146f3d-9c65-4b6c-c6d9-e77999d63d94"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(17936, 30) (4484, 30)\n"
          ]
        }
      ],
      "source": [
        "from tensorflow.keras.preprocessing import sequence\n",
        "max_words = 30\n",
        "X_train = sequence.pad_sequences(X_train, maxlen=max_words)\n",
        "X_test = sequence.pad_sequences(X_test, maxlen=max_words)\n",
        "print(X_train.shape,X_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "96e90d44",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:42.837758Z",
          "iopub.status.busy": "2022-02-03T01:56:42.837018Z",
          "iopub.status.idle": "2022-02-03T01:56:43.235255Z",
          "shell.execute_reply": "2022-02-03T01:56:43.234582Z",
          "shell.execute_reply.started": "2022-02-03T01:33:40.507862Z"
        },
        "papermill": {
          "duration": 0.651433,
          "end_time": "2022-02-03T01:56:43.235415",
          "exception": false,
          "start_time": "2022-02-03T01:56:42.583982",
          "status": "completed"
        },
        "tags": [],
        "id": "96e90d44",
        "outputId": "33ba66be-b7b7-411e-c3f2-c5c6ac467ec6"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n",
            "User settings:\n",
            "\n",
            "   KMP_AFFINITY=granularity=fine,noverbose,compact,1,0\n",
            "   KMP_BLOCKTIME=0\n",
            "   KMP_DUPLICATE_LIB_OK=True\n",
            "   KMP_INIT_AT_FORK=FALSE\n",
            "   KMP_SETTINGS=1\n",
            "   KMP_WARNINGS=0\n",
            "\n",
            "Effective settings:\n",
            "\n",
            "   KMP_ABORT_DELAY=0\n",
            "   KMP_ADAPTIVE_LOCK_PROPS='1,1024'\n",
            "   KMP_ALIGN_ALLOC=64\n",
            "   KMP_ALL_THREADPRIVATE=128\n",
            "   KMP_ATOMIC_MODE=2\n",
            "   KMP_BLOCKTIME=0\n",
            "   KMP_CPUINFO_FILE: value is not defined\n",
            "   KMP_DETERMINISTIC_REDUCTION=false\n",
            "   KMP_DEVICE_THREAD_LIMIT=2147483647\n",
            "   KMP_DISP_NUM_BUFFERS=7\n",
            "   KMP_DUPLICATE_LIB_OK=true\n",
            "   KMP_ENABLE_TASK_THROTTLING=true\n",
            "   KMP_FORCE_REDUCTION: value is not defined\n",
            "   KMP_FOREIGN_THREADS_THREADPRIVATE=true\n",
            "   KMP_FORKJOIN_BARRIER='2,2'\n",
            "   KMP_FORKJOIN_BARRIER_PATTERN='hyper,hyper'\n",
            "   KMP_GTID_MODE=3\n",
            "   KMP_HANDLE_SIGNALS=false\n",
            "   KMP_HOT_TEAMS_MAX_LEVEL=1\n",
            "   KMP_HOT_TEAMS_MODE=0\n",
            "   KMP_INIT_AT_FORK=true\n",
            "   KMP_LIBRARY=throughput\n",
            "   KMP_LOCK_KIND=queuing\n",
            "   KMP_MALLOC_POOL_INCR=1M\n",
            "   KMP_NUM_LOCKS_IN_BLOCK=1\n",
            "   KMP_PLAIN_BARRIER='2,2'\n",
            "   KMP_PLAIN_BARRIER_PATTERN='hyper,hyper'\n",
            "   KMP_REDUCTION_BARRIER='1,1'\n",
            "   KMP_REDUCTION_BARRIER_PATTERN='hyper,hyper'\n",
            "   KMP_SCHEDULE='static,balanced;guided,iterative'\n",
            "   KMP_SETTINGS=true\n",
            "   KMP_SPIN_BACKOFF_PARAMS='4096,100'\n",
            "   KMP_STACKOFFSET=64\n",
            "   KMP_STACKPAD=0\n",
            "   KMP_STACKSIZE=8M\n",
            "   KMP_STORAGE_MAP=false\n",
            "   KMP_TASKING=2\n",
            "   KMP_TASKLOOP_MIN_TASKS=0\n",
            "   KMP_TASK_STEALING_CONSTRAINT=1\n",
            "   KMP_TEAMS_THREAD_LIMIT=4\n",
            "   KMP_TOPOLOGY_METHOD=all\n",
            "   KMP_USE_YIELD=1\n",
            "   KMP_VERSION=false\n",
            "   KMP_WARNINGS=false\n",
            "   OMP_AFFINITY_FORMAT='OMP: pid %P tid %i thread %n bound to OS proc set {%A}'\n",
            "   OMP_ALLOCATOR=omp_default_mem_alloc\n",
            "   OMP_CANCELLATION=false\n",
            "   OMP_DEFAULT_DEVICE=0\n",
            "   OMP_DISPLAY_AFFINITY=false\n",
            "   OMP_DISPLAY_ENV=false\n",
            "   OMP_DYNAMIC=false\n",
            "   OMP_MAX_ACTIVE_LEVELS=1\n",
            "   OMP_MAX_TASK_PRIORITY=0\n",
            "   OMP_NESTED: deprecated; max-active-levels-var=1\n",
            "   OMP_NUM_THREADS: value is not defined\n",
            "   OMP_PLACES: value is not defined\n",
            "   OMP_PROC_BIND='intel'\n",
            "   OMP_SCHEDULE='static'\n",
            "   OMP_STACKSIZE=8M\n",
            "   OMP_TARGET_OFFLOAD=DEFAULT\n",
            "   OMP_THREAD_LIMIT=2147483647\n",
            "   OMP_WAIT_POLICY=PASSIVE\n",
            "   KMP_AFFINITY='noverbose,warnings,respect,granularity=fine,compact,1,0'\n",
            "\n",
            "2022-02-03 01:56:42.884030: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "embedding (Embedding)        (None, 30, 100)           2000000   \n",
            "_________________________________________________________________\n",
            "conv1d (Conv1D)              (None, 30, 32)            9632      \n",
            "_________________________________________________________________\n",
            "max_pooling1d (MaxPooling1D) (None, 15, 32)            0         \n",
            "_________________________________________________________________\n",
            "conv1d_1 (Conv1D)            (None, 15, 32)            3104      \n",
            "_________________________________________________________________\n",
            "max_pooling1d_1 (MaxPooling1 (None, 7, 32)             0         \n",
            "_________________________________________________________________\n",
            "lstm (LSTM)                  (None, 100)               53200     \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 3)                 303       \n",
            "=================================================================\n",
            "Total params: 2,066,239\n",
            "Trainable params: 2,066,239\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "import tensorflow.keras.backend as K\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Dense,Embedding,Conv1D,MaxPooling1D,LSTM\n",
        "from sklearn.metrics import accuracy_score,confusion_matrix,classification_report\n",
        "\n",
        "batch_size = 128\n",
        "epochs = 10\n",
        "\n",
        "max_features = 20000\n",
        "embed_dim = 100\n",
        "\n",
        "np.random.seed(seed)\n",
        "K.clear_session()\n",
        "model = Sequential()\n",
        "model.add(Embedding(max_features, embed_dim, input_length=X_train.shape[1]))\n",
        "model.add(Conv1D(filters=32, kernel_size=3, padding='same', activation='relu'))\n",
        "model.add(MaxPooling1D(pool_size=2))\n",
        "model.add(Conv1D(filters=32, kernel_size=3, padding='same', activation='relu'))\n",
        "model.add(MaxPooling1D(pool_size=2))    \n",
        "model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2))\n",
        "model.add(Dense(num_classes, activation='softmax'))\n",
        "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
        "model.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "37444a14",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:43.732154Z",
          "iopub.status.busy": "2022-02-03T01:56:43.731196Z",
          "iopub.status.idle": "2022-02-03T01:56:44.873786Z",
          "shell.execute_reply": "2022-02-03T01:56:44.873092Z",
          "shell.execute_reply.started": "2022-02-03T01:33:42.533137Z"
        },
        "papermill": {
          "duration": 1.39359,
          "end_time": "2022-02-03T01:56:44.873940",
          "exception": false,
          "start_time": "2022-02-03T01:56:43.480350",
          "status": "completed"
        },
        "tags": [],
        "id": "37444a14",
        "outputId": "45389a7c-07eb-4235-ded2-3d1cf85dc4de"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "execution_count": 36,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tf.keras.utils.plot_model(model, show_shapes=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "2a7215e3",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:56:45.383519Z",
          "iopub.status.busy": "2022-02-03T01:56:45.382780Z",
          "iopub.status.idle": "2022-02-03T01:58:19.413604Z",
          "shell.execute_reply": "2022-02-03T01:58:19.412979Z",
          "shell.execute_reply.started": "2022-02-03T01:33:44.626419Z"
        },
        "papermill": {
          "duration": 94.287806,
          "end_time": "2022-02-03T01:58:19.413798",
          "exception": false,
          "start_time": "2022-02-03T01:56:45.125992",
          "status": "completed"
        },
        "tags": [],
        "id": "2a7215e3",
        "outputId": "d8848cf5-abb5-49b5-9281-5e57521651bb"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "2022-02-03 01:56:45.462012: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "141/141 - 14s - loss: 0.6622 - accuracy: 0.7189 - val_loss: 0.4014 - val_accuracy: 0.8533\n",
            "Epoch 2/10\n",
            "141/141 - 9s - loss: 0.2332 - accuracy: 0.9215 - val_loss: 0.2251 - val_accuracy: 0.9266\n",
            "Epoch 3/10\n",
            "141/141 - 9s - loss: 0.0742 - accuracy: 0.9783 - val_loss: 0.2399 - val_accuracy: 0.9338\n",
            "Epoch 4/10\n",
            "141/141 - 8s - loss: 0.0313 - accuracy: 0.9924 - val_loss: 0.2399 - val_accuracy: 0.9306\n",
            "Epoch 5/10\n",
            "141/141 - 9s - loss: 0.0207 - accuracy: 0.9948 - val_loss: 0.2970 - val_accuracy: 0.9331\n",
            "Epoch 6/10\n",
            "141/141 - 9s - loss: 0.0140 - accuracy: 0.9961 - val_loss: 0.2875 - val_accuracy: 0.9338\n",
            "Epoch 7/10\n",
            "141/141 - 10s - loss: 0.0109 - accuracy: 0.9973 - val_loss: 0.3232 - val_accuracy: 0.9300\n",
            "Epoch 8/10\n",
            "141/141 - 9s - loss: 0.0076 - accuracy: 0.9980 - val_loss: 0.3296 - val_accuracy: 0.9340\n",
            "Epoch 9/10\n",
            "141/141 - 9s - loss: 0.0084 - accuracy: 0.9977 - val_loss: 0.3596 - val_accuracy: 0.9309\n",
            "Epoch 10/10\n",
            "141/141 - 9s - loss: 0.0056 - accuracy: 0.9986 - val_loss: 0.3547 - val_accuracy: 0.9347\n"
          ]
        }
      ],
      "source": [
        "history = model.fit(X_train, y_train, validation_data=(X_test, y_test), \n",
        "                          epochs=epochs, batch_size=batch_size, verbose=2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9b5b93e2",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:19.930906Z",
          "iopub.status.busy": "2022-02-03T01:58:19.929897Z",
          "iopub.status.idle": "2022-02-03T01:58:20.314009Z",
          "shell.execute_reply": "2022-02-03T01:58:20.314641Z",
          "shell.execute_reply.started": "2022-02-03T01:19:30.095594Z"
        },
        "papermill": {
          "duration": 0.645581,
          "end_time": "2022-02-03T01:58:20.314845",
          "exception": false,
          "start_time": "2022-02-03T01:58:19.669264",
          "status": "completed"
        },
        "tags": [],
        "id": "9b5b93e2",
        "outputId": "e8f7b071-454d-4665-c2d8-38fa230aa9d4"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "def plot_training_hist(history):\n",
        "    '''Function to plot history for accuracy and loss'''\n",
        "    \n",
        "    fig, ax = plt.subplots(1,2, figsize=(10,4))\n",
        "    # first plot\n",
        "    ax[0].plot(history.history['accuracy'])\n",
        "    ax[0].plot(history.history['val_accuracy'])\n",
        "    ax[0].set_title('Model Accuracy')\n",
        "    ax[0].set_xlabel('epoch')\n",
        "    ax[0].set_ylabel('accuracy')\n",
        "    ax[0].legend(['train', 'validation'], loc='best')\n",
        "    \n",
        "    # second plot\n",
        "    ax[1].plot(history.history['loss'])\n",
        "    ax[1].plot(history.history['val_loss'])\n",
        "    ax[1].set_title('Model Loss')\n",
        "    ax[1].set_xlabel('epoch')\n",
        "    ax[1].set_ylabel('loss')\n",
        "    ax[1].legend(['train', 'validation'], loc='best')\n",
        "    \n",
        "plot_training_hist(history)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "aca886b9",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:20.826337Z",
          "iopub.status.busy": "2022-02-03T01:58:20.825293Z",
          "iopub.status.idle": "2022-02-03T01:58:22.440467Z",
          "shell.execute_reply": "2022-02-03T01:58:22.441150Z",
          "shell.execute_reply.started": "2022-02-03T01:35:22.739767Z"
        },
        "papermill": {
          "duration": 1.873611,
          "end_time": "2022-02-03T01:58:22.441337",
          "exception": false,
          "start_time": "2022-02-03T01:58:20.567726",
          "status": "completed"
        },
        "tags": [],
        "id": "aca886b9",
        "outputId": "e3da2daa-0774-4af6-a6a0-a7937144701c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy:\t93.5%\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.84      0.78      0.81       478\n",
            "           1       0.94      0.95      0.95      1782\n",
            "           2       0.95      0.95      0.95      2224\n",
            "\n",
            "    accuracy                           0.93      4484\n",
            "   macro avg       0.91      0.90      0.90      4484\n",
            "weighted avg       0.93      0.93      0.93      4484\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# predict class with test set\n",
        "y_pred_test =  np.argmax(model.predict(X_test), axis=1)\n",
        "print('Accuracy:\\t{:0.1f}%'.format(accuracy_score(np.argmax(y_test,axis=1),y_pred_test)*100))\n",
        "print(classification_report(np.argmax(y_test,axis=1), y_pred_test))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "afbd244e",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:22.952437Z",
          "iopub.status.busy": "2022-02-03T01:58:22.951248Z",
          "iopub.status.idle": "2022-02-03T01:58:24.565927Z",
          "shell.execute_reply": "2022-02-03T01:58:24.565269Z",
          "shell.execute_reply.started": "2022-02-03T01:35:34.028374Z"
        },
        "papermill": {
          "duration": 1.872051,
          "end_time": "2022-02-03T01:58:24.566072",
          "exception": false,
          "start_time": "2022-02-03T01:58:22.694021",
          "status": "completed"
        },
        "tags": [],
        "id": "afbd244e",
        "outputId": "648ed9da-62f1-422e-9d86-dc29b5820136"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "2    2224\n",
            "1    1782\n",
            "0     478\n",
            "dtype: int64\n",
            "2    2240\n",
            "1    1800\n",
            "0     444\n",
            "dtype: int64\n"
          ]
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "from sklearn.metrics import confusion_matrix\n",
        "import seaborn as sns \n",
        "def plot_confusion_matrix(model, X_test, y_test):\n",
        "    '''Function to plot confusion matrix for the passed model and the data'''\n",
        "    \n",
        "    sentiment_classes = ['Negative','Neutral', 'Positive']\n",
        "    # use model to do the prediction\n",
        "    y_pred = model.predict(X_test)\n",
        "    # compute confusion matrix\n",
        "    cm = confusion_matrix(np.argmax(y_pred, axis=1),np.argmax(np.array(y_test),axis=1))\n",
        "    \n",
        "    print(pd.Series(np.argmax(np.array(y_test),axis=1)).value_counts())\n",
        "    print(pd.Series(np.argmax(y_pred, axis=1)).value_counts())\n",
        "    \n",
        "    # plot confusion matrix\n",
        "    plt.figure(figsize=(8,6))\n",
        "    sns.heatmap(cm, cmap=plt.cm.Blues, annot=True, fmt='d', \n",
        "                xticklabels=sentiment_classes,\n",
        "                yticklabels=sentiment_classes)\n",
        "    plt.title('Confusion matrix', fontsize=16)\n",
        "    plt.xlabel('Actual label', fontsize=12)\n",
        "    plt.ylabel('Predicted label', fontsize=12)\n",
        "    \n",
        "plot_confusion_matrix(model, X_test, y_test)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "3436a227",
      "metadata": {
        "papermill": {
          "duration": 0.256412,
          "end_time": "2022-02-03T01:58:25.078309",
          "exception": false,
          "start_time": "2022-02-03T01:58:24.821897",
          "status": "completed"
        },
        "tags": [],
        "id": "3436a227"
      },
      "source": [
        "## Model2 "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "69c12e7c",
      "metadata": {
        "execution": {
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          "shell.execute_reply.started": "2022-02-03T01:35:49.239956Z"
        },
        "papermill": {
          "duration": 1.491428,
          "end_time": "2022-02-03T01:58:26.824610",
          "exception": false,
          "start_time": "2022-02-03T01:58:25.333182",
          "status": "completed"
        },
        "tags": [],
        "id": "69c12e7c",
        "outputId": "f8af4a7f-3926-4cfc-e3ad-2d9c1d857c99"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Before Tokenization & Padding \n",
            " nice project ortcoin ort okratech bitcoin airdrop freelancer crypto dRywbnSVCo\n",
            "After Tokenization & Padding \n",
            " [ 204    5 2119 1795 2120    1   11 1735    3    0    0    0    0    0\n",
            "    0    0    0    0    0    0    0    0    0    0    0    0    0    0\n",
            "    0    0    0    0    0    0    0    0    0    0    0    0    0    0\n",
            "    0    0    0    0    0    0    0    0]\n"
          ]
        }
      ],
      "source": [
        "from tensorflow.keras.preprocessing.text import Tokenizer\n",
        "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
        "\n",
        "max_words = 5000\n",
        "max_len=50\n",
        "\n",
        "def tokenize_pad_sequences(text):\n",
        "    '''\n",
        "    This function tokenize the input text into sequnences of intergers and then\n",
        "    pad each sequence to the same length\n",
        "    '''\n",
        "    # Text tokenization\n",
        "    tokenizer = Tokenizer(num_words=max_words, lower=True, split=' ')\n",
        "    tokenizer.fit_on_texts(text)\n",
        "    # Transforms text to a sequence of integers\n",
        "    X = tokenizer.texts_to_sequences(text)\n",
        "    # Pad sequences to the same length\n",
        "    X = pad_sequences(X, padding='post', maxlen=max_len)\n",
        "    # return sequences\n",
        "    return X, tokenizer\n",
        "\n",
        "print('Before Tokenization & Padding \\n', df['cleaned_tweets'][0])\n",
        "X, tokenizer = tokenize_pad_sequences(df['cleaned_tweets'])\n",
        "print('After Tokenization & Padding \\n', X[0])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "0b8cebb4",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:27.341845Z",
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          "shell.execute_reply": "2022-02-03T01:58:27.361208Z",
          "shell.execute_reply.started": "2022-02-03T01:43:30.088259Z"
        },
        "papermill": {
          "duration": 0.278241,
          "end_time": "2022-02-03T01:58:27.361384",
          "exception": false,
          "start_time": "2022-02-03T01:58:27.083143",
          "status": "completed"
        },
        "tags": [],
        "id": "0b8cebb4",
        "outputId": "eb5920c0-5eb2-48e8-a77b-ddbdc9e259d5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Train Set:  (13452, 50) (13452, 3)\n",
            "Validation Set:  (4484, 50) (4484, 3)\n",
            "Test Set:  (4484, 50) (4484, 3)\n"
          ]
        }
      ],
      "source": [
        "y = pd.get_dummies(df['sentiment'])\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=10)\n",
        "X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=0.25, random_state=1)\n",
        "print('Train Set: ', X_train.shape, y_train.shape)\n",
        "print('Validation Set: ', X_val.shape, y_val.shape)\n",
        "print('Test Set: ', X_test.shape, y_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a7e38a12",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:27.886789Z",
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          "shell.execute_reply": "2022-02-03T01:58:27.888629Z",
          "shell.execute_reply.started": "2022-02-03T01:43:54.298137Z"
        },
        "papermill": {
          "duration": 0.267738,
          "end_time": "2022-02-03T01:58:27.888854",
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          "start_time": "2022-02-03T01:58:27.621116",
          "status": "completed"
        },
        "tags": [],
        "id": "a7e38a12"
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      "outputs": [],
      "source": [
        "import tensorflow.keras.backend as K\n",
        "\n",
        "def f1_score(precision, recall):\n",
        "    ''' Function to calculate f1 score '''\n",
        "    \n",
        "    f1_val = 2*(precision*recall)/(precision+recall+K.epsilon())\n",
        "    return f1_val"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "473cc5e0",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:28.408957Z",
          "iopub.status.busy": "2022-02-03T01:58:28.408176Z",
          "iopub.status.idle": "2022-02-03T01:58:28.415180Z",
          "shell.execute_reply": "2022-02-03T01:58:28.415756Z",
          "shell.execute_reply.started": "2022-02-03T01:43:58.030594Z"
        },
        "papermill": {
          "duration": 0.268853,
          "end_time": "2022-02-03T01:58:28.415949",
          "exception": false,
          "start_time": "2022-02-03T01:58:28.147096",
          "status": "completed"
        },
        "tags": [],
        "id": "473cc5e0"
      },
      "outputs": [],
      "source": [
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Embedding, Conv1D, MaxPooling1D, Bidirectional, LSTM, Dense, Dropout\n",
        "from tensorflow.keras.metrics import Precision, Recall\n",
        "from tensorflow.keras.optimizers import SGD\n",
        "from tensorflow.keras.optimizers import RMSprop\n",
        "from tensorflow.keras import datasets\n",
        "from tensorflow.keras.callbacks import LearningRateScheduler\n",
        "from tensorflow.keras.callbacks import History\n",
        "from tensorflow.keras import losses"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5ffbe018",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:28.935597Z",
          "iopub.status.busy": "2022-02-03T01:58:28.934757Z",
          "iopub.status.idle": "2022-02-03T01:58:28.937854Z",
          "shell.execute_reply": "2022-02-03T01:58:28.937180Z",
          "shell.execute_reply.started": "2022-02-03T01:44:50.435362Z"
        },
        "papermill": {
          "duration": 0.264408,
          "end_time": "2022-02-03T01:58:28.937999",
          "exception": false,
          "start_time": "2022-02-03T01:58:28.673591",
          "status": "completed"
        },
        "tags": [],
        "id": "5ffbe018"
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      "outputs": [],
      "source": [
        "vocab_size = 5000\n",
        "embedding_size = 32\n",
        "epochs = 50\n",
        "learning_rate = 0.01\n",
        "decay_rate = learning_rate / epochs\n",
        "momentum = 0.8"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "aa61d0c4",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:29.458130Z",
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          "shell.execute_reply.started": "2022-02-03T01:44:52.028089Z"
        },
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          "duration": 0.764847,
          "end_time": "2022-02-03T01:58:29.961693",
          "exception": false,
          "start_time": "2022-02-03T01:58:29.196846",
          "status": "completed"
        },
        "tags": [],
        "id": "aa61d0c4"
      },
      "outputs": [],
      "source": [
        "sgd = SGD(learning_rate=learning_rate, momentum=momentum, decay=decay_rate, nesterov=False)\n",
        "# Build model\n",
        "model= Sequential()\n",
        "model.add(Embedding(vocab_size, embedding_size, input_length=max_len))\n",
        "model.add(Conv1D(filters=32, kernel_size=1, padding='same', activation='relu'))\n",
        "model.add(MaxPooling1D(pool_size=2))\n",
        "model.add(Bidirectional(LSTM(32)))\n",
        "model.add(Dropout(0.4))\n",
        "model.add(Dense(3, activation='softmax'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c2ae1495",
      "metadata": {
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      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "execution_count": 47,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tf.keras.utils.plot_model(model, show_shapes=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "df699e5a",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:31.302375Z",
          "iopub.status.busy": "2022-02-03T01:58:31.301674Z",
          "iopub.status.idle": "2022-02-03T01:58:31.316853Z",
          "shell.execute_reply": "2022-02-03T01:58:31.316156Z",
          "shell.execute_reply.started": "2022-02-03T01:44:54.052017Z"
        },
        "papermill": {
          "duration": 0.347609,
          "end_time": "2022-02-03T01:58:31.317010",
          "exception": false,
          "start_time": "2022-02-03T01:58:30.969401",
          "status": "completed"
        },
        "tags": [],
        "id": "df699e5a"
      },
      "outputs": [],
      "source": [
        "model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy', Precision(), Recall()])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4194adcc",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T01:58:31.846331Z",
          "iopub.status.busy": "2022-02-03T01:58:31.845530Z",
          "iopub.status.idle": "2022-02-03T02:04:00.277785Z",
          "shell.execute_reply": "2022-02-03T02:04:00.278350Z",
          "shell.execute_reply.started": "2022-02-03T01:44:56.751101Z"
        },
        "papermill": {
          "duration": 328.699171,
          "end_time": "2022-02-03T02:04:00.278585",
          "exception": false,
          "start_time": "2022-02-03T01:58:31.579414",
          "status": "completed"
        },
        "tags": [],
        "id": "4194adcc",
        "outputId": "098a9173-ec6f-47df-d807-692ca148009b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/50\n",
            "106/106 [==============================] - 12s 65ms/step - loss: 0.9725 - accuracy: 0.4983 - precision: 0.5279 - recall: 0.1401 - val_loss: 0.9532 - val_accuracy: 0.4931 - val_precision: 0.6894 - val_recall: 0.2183\n",
            "Epoch 2/50\n",
            "106/106 [==============================] - 6s 54ms/step - loss: 0.9462 - accuracy: 0.5101 - precision: 0.5526 - recall: 0.2829 - val_loss: 0.9451 - val_accuracy: 0.4931 - val_precision: 0.6302 - val_recall: 0.3492\n",
            "Epoch 3/50\n",
            "106/106 [==============================] - 6s 59ms/step - loss: 0.9340 - accuracy: 0.5387 - precision: 0.6050 - recall: 0.3062 - val_loss: 0.9237 - val_accuracy: 0.5865 - val_precision: 0.6547 - val_recall: 0.3247\n",
            "Epoch 4/50\n",
            "106/106 [==============================] - 6s 53ms/step - loss: 0.9063 - accuracy: 0.5914 - precision: 0.6471 - recall: 0.4066 - val_loss: 0.8900 - val_accuracy: 0.6010 - val_precision: 0.6440 - val_recall: 0.4902\n",
            "Epoch 5/50\n",
            "106/106 [==============================] - 6s 55ms/step - loss: 0.8852 - accuracy: 0.6069 - precision: 0.6462 - recall: 0.4969 - val_loss: 0.8794 - val_accuracy: 0.6084 - val_precision: 0.6391 - val_recall: 0.5025\n",
            "Epoch 6/50\n",
            "106/106 [==============================] - 6s 56ms/step - loss: 0.8770 - accuracy: 0.6139 - precision: 0.6461 - recall: 0.5043 - val_loss: 0.8712 - val_accuracy: 0.6115 - val_precision: 0.6382 - val_recall: 0.5196\n",
            "Epoch 7/50\n",
            "106/106 [==============================] - 6s 54ms/step - loss: 0.8667 - accuracy: 0.6191 - precision: 0.6537 - recall: 0.5175 - val_loss: 0.8634 - val_accuracy: 0.6108 - val_precision: 0.6474 - val_recall: 0.5294\n",
            "Epoch 8/50\n",
            "106/106 [==============================] - 6s 59ms/step - loss: 0.8535 - accuracy: 0.6262 - precision: 0.6629 - recall: 0.5309 - val_loss: 0.8503 - val_accuracy: 0.6285 - val_precision: 0.6544 - val_recall: 0.5292\n",
            "Epoch 9/50\n",
            "106/106 [==============================] - 6s 53ms/step - loss: 0.8413 - accuracy: 0.6366 - precision: 0.6738 - recall: 0.5413 - val_loss: 0.8342 - val_accuracy: 0.6343 - val_precision: 0.6730 - val_recall: 0.5508\n",
            "Epoch 10/50\n",
            "106/106 [==============================] - 6s 55ms/step - loss: 0.8214 - accuracy: 0.6512 - precision: 0.6901 - recall: 0.5565 - val_loss: 0.8184 - val_accuracy: 0.6474 - val_precision: 0.6778 - val_recall: 0.5680\n",
            "Epoch 11/50\n",
            "106/106 [==============================] - 6s 52ms/step - loss: 0.8046 - accuracy: 0.6612 - precision: 0.7042 - recall: 0.5726 - val_loss: 0.7991 - val_accuracy: 0.6684 - val_precision: 0.7078 - val_recall: 0.5850\n",
            "Epoch 12/50\n",
            "106/106 [==============================] - 6s 53ms/step - loss: 0.7814 - accuracy: 0.6825 - precision: 0.7245 - recall: 0.5942 - val_loss: 0.7816 - val_accuracy: 0.6789 - val_precision: 0.7234 - val_recall: 0.6015\n",
            "Epoch 13/50\n",
            "106/106 [==============================] - 6s 52ms/step - loss: 0.7548 - accuracy: 0.6968 - precision: 0.7437 - recall: 0.6140 - val_loss: 0.7509 - val_accuracy: 0.7016 - val_precision: 0.7397 - val_recall: 0.6305\n",
            "Epoch 14/50\n",
            "106/106 [==============================] - 6s 58ms/step - loss: 0.7239 - accuracy: 0.7218 - precision: 0.7673 - recall: 0.6449 - val_loss: 0.7157 - val_accuracy: 0.7228 - val_precision: 0.7600 - val_recall: 0.6617\n",
            "Epoch 15/50\n",
            "106/106 [==============================] - 6s 59ms/step - loss: 0.6894 - accuracy: 0.7423 - precision: 0.7852 - recall: 0.6734 - val_loss: 0.7046 - val_accuracy: 0.7152 - val_precision: 0.7471 - val_recall: 0.6661\n",
            "Epoch 16/50\n",
            "106/106 [==============================] - 6s 60ms/step - loss: 0.6537 - accuracy: 0.7622 - precision: 0.8027 - recall: 0.7023 - val_loss: 0.6470 - val_accuracy: 0.7571 - val_precision: 0.7988 - val_recall: 0.7092\n",
            "Epoch 17/50\n",
            "106/106 [==============================] - 7s 63ms/step - loss: 0.6163 - accuracy: 0.7803 - precision: 0.8182 - recall: 0.7292 - val_loss: 0.6225 - val_accuracy: 0.7685 - val_precision: 0.8001 - val_recall: 0.7302\n",
            "Epoch 18/50\n",
            "106/106 [==============================] - 6s 60ms/step - loss: 0.5838 - accuracy: 0.7951 - precision: 0.8300 - recall: 0.7523 - val_loss: 0.6106 - val_accuracy: 0.7721 - val_precision: 0.7939 - val_recall: 0.7424\n",
            "Epoch 19/50\n",
            "106/106 [==============================] - 6s 61ms/step - loss: 0.5555 - accuracy: 0.8078 - precision: 0.8446 - recall: 0.7703 - val_loss: 0.6001 - val_accuracy: 0.7734 - val_precision: 0.7936 - val_recall: 0.7493\n",
            "Epoch 20/50\n",
            "106/106 [==============================] - 6s 58ms/step - loss: 0.5267 - accuracy: 0.8188 - precision: 0.8531 - recall: 0.7861 - val_loss: 0.5507 - val_accuracy: 0.8091 - val_precision: 0.8403 - val_recall: 0.7756\n",
            "Epoch 21/50\n",
            "106/106 [==============================] - 6s 55ms/step - loss: 0.5009 - accuracy: 0.8310 - precision: 0.8613 - recall: 0.8023 - val_loss: 0.5703 - val_accuracy: 0.7904 - val_precision: 0.8043 - val_recall: 0.7674\n",
            "Epoch 22/50\n",
            "106/106 [==============================] - 6s 59ms/step - loss: 0.4805 - accuracy: 0.8374 - precision: 0.8680 - recall: 0.8117 - val_loss: 0.4982 - val_accuracy: 0.8258 - val_precision: 0.8545 - val_recall: 0.8040\n",
            "Epoch 23/50\n",
            "106/106 [==============================] - 6s 57ms/step - loss: 0.4601 - accuracy: 0.8441 - precision: 0.8726 - recall: 0.8192 - val_loss: 0.4872 - val_accuracy: 0.8263 - val_precision: 0.8517 - val_recall: 0.8066\n",
            "Epoch 24/50\n",
            "106/106 [==============================] - 6s 57ms/step - loss: 0.4355 - accuracy: 0.8499 - precision: 0.8810 - recall: 0.8288 - val_loss: 0.4680 - val_accuracy: 0.8347 - val_precision: 0.8609 - val_recall: 0.8142\n",
            "Epoch 25/50\n",
            "106/106 [==============================] - 8s 72ms/step - loss: 0.4130 - accuracy: 0.8568 - precision: 0.8877 - recall: 0.8376 - val_loss: 0.4626 - val_accuracy: 0.8332 - val_precision: 0.8641 - val_recall: 0.8100\n",
            "Epoch 26/50\n",
            "106/106 [==============================] - 7s 62ms/step - loss: 0.3953 - accuracy: 0.8607 - precision: 0.8905 - recall: 0.8424 - val_loss: 0.4414 - val_accuracy: 0.8408 - val_precision: 0.8713 - val_recall: 0.8200\n",
            "Epoch 27/50\n",
            "106/106 [==============================] - 7s 66ms/step - loss: 0.3767 - accuracy: 0.8664 - precision: 0.9005 - recall: 0.8507 - val_loss: 0.4339 - val_accuracy: 0.8437 - val_precision: 0.8763 - val_recall: 0.8229\n",
            "Epoch 28/50\n",
            "106/106 [==============================] - 6s 58ms/step - loss: 0.3630 - accuracy: 0.8698 - precision: 0.9012 - recall: 0.8527 - val_loss: 0.4235 - val_accuracy: 0.8490 - val_precision: 0.8812 - val_recall: 0.8240\n",
            "Epoch 29/50\n",
            "106/106 [==============================] - 8s 79ms/step - loss: 0.3472 - accuracy: 0.8730 - precision: 0.9078 - recall: 0.8589 - val_loss: 0.4131 - val_accuracy: 0.8497 - val_precision: 0.8789 - val_recall: 0.8334\n",
            "Epoch 30/50\n",
            "106/106 [==============================] - 8s 75ms/step - loss: 0.3378 - accuracy: 0.8764 - precision: 0.9098 - recall: 0.8610 - val_loss: 0.5792 - val_accuracy: 0.7924 - val_precision: 0.8516 - val_recall: 0.7232\n",
            "Epoch 31/50\n",
            "106/106 [==============================] - 7s 62ms/step - loss: 0.3322 - accuracy: 0.8799 - precision: 0.9111 - recall: 0.8612 - val_loss: 0.4079 - val_accuracy: 0.8550 - val_precision: 0.8888 - val_recall: 0.8341\n",
            "Epoch 32/50\n",
            "106/106 [==============================] - 6s 58ms/step - loss: 0.3185 - accuracy: 0.8832 - precision: 0.9151 - recall: 0.8667 - val_loss: 0.3996 - val_accuracy: 0.8595 - val_precision: 0.8918 - val_recall: 0.8361\n",
            "Epoch 33/50\n",
            "106/106 [==============================] - 7s 62ms/step - loss: 0.3082 - accuracy: 0.8892 - precision: 0.9188 - recall: 0.8659 - val_loss: 0.4801 - val_accuracy: 0.8267 - val_precision: 0.8702 - val_recall: 0.7910\n",
            "Epoch 34/50\n",
            "106/106 [==============================] - 7s 68ms/step - loss: 0.3027 - accuracy: 0.8918 - precision: 0.9187 - recall: 0.8689 - val_loss: 0.4119 - val_accuracy: 0.8568 - val_precision: 0.8886 - val_recall: 0.8341\n",
            "Epoch 35/50\n",
            "106/106 [==============================] - 7s 64ms/step - loss: 0.2946 - accuracy: 0.8945 - precision: 0.9236 - recall: 0.8711 - val_loss: 0.3914 - val_accuracy: 0.8682 - val_precision: 0.8929 - val_recall: 0.8388\n",
            "Epoch 36/50\n",
            "106/106 [==============================] - 6s 61ms/step - loss: 0.2864 - accuracy: 0.8996 - precision: 0.9241 - recall: 0.8712 - val_loss: 0.3988 - val_accuracy: 0.8651 - val_precision: 0.8937 - val_recall: 0.8379\n",
            "Epoch 37/50\n",
            "106/106 [==============================] - 6s 59ms/step - loss: 0.2783 - accuracy: 0.9039 - precision: 0.9270 - recall: 0.8765 - val_loss: 0.3999 - val_accuracy: 0.8662 - val_precision: 0.8867 - val_recall: 0.8432\n",
            "Epoch 38/50\n",
            "106/106 [==============================] - 6s 57ms/step - loss: 0.2742 - accuracy: 0.9067 - precision: 0.9269 - recall: 0.8795 - val_loss: 0.4030 - val_accuracy: 0.8689 - val_precision: 0.8916 - val_recall: 0.8379\n",
            "Epoch 39/50\n",
            "106/106 [==============================] - 7s 63ms/step - loss: 0.2699 - accuracy: 0.9083 - precision: 0.9280 - recall: 0.8824 - val_loss: 0.3934 - val_accuracy: 0.8753 - val_precision: 0.8945 - val_recall: 0.8455\n",
            "Epoch 40/50\n",
            "106/106 [==============================] - 7s 62ms/step - loss: 0.2638 - accuracy: 0.9150 - precision: 0.9324 - recall: 0.8867 - val_loss: 0.4062 - val_accuracy: 0.8675 - val_precision: 0.8843 - val_recall: 0.8492\n",
            "Epoch 41/50\n",
            "106/106 [==============================] - 7s 61ms/step - loss: 0.2578 - accuracy: 0.9159 - precision: 0.9328 - recall: 0.8890 - val_loss: 0.4076 - val_accuracy: 0.8686 - val_precision: 0.8889 - val_recall: 0.8441\n",
            "Epoch 42/50\n",
            "106/106 [==============================] - 8s 72ms/step - loss: 0.2524 - accuracy: 0.9202 - precision: 0.9369 - recall: 0.8933 - val_loss: 0.3954 - val_accuracy: 0.8738 - val_precision: 0.8892 - val_recall: 0.8519\n",
            "Epoch 43/50\n",
            "106/106 [==============================] - 8s 75ms/step - loss: 0.2476 - accuracy: 0.9242 - precision: 0.9369 - recall: 0.8970 - val_loss: 0.3943 - val_accuracy: 0.8778 - val_precision: 0.8919 - val_recall: 0.8539\n",
            "Epoch 44/50\n",
            "106/106 [==============================] - 7s 65ms/step - loss: 0.2449 - accuracy: 0.9249 - precision: 0.9358 - recall: 0.8988 - val_loss: 0.4020 - val_accuracy: 0.8767 - val_precision: 0.8915 - val_recall: 0.8537\n",
            "Epoch 45/50\n",
            "106/106 [==============================] - 7s 64ms/step - loss: 0.2420 - accuracy: 0.9264 - precision: 0.9398 - recall: 0.9031 - val_loss: 0.4006 - val_accuracy: 0.8751 - val_precision: 0.8904 - val_recall: 0.8550\n",
            "Epoch 46/50\n",
            "106/106 [==============================] - 7s 62ms/step - loss: 0.2378 - accuracy: 0.9287 - precision: 0.9399 - recall: 0.9061 - val_loss: 0.4086 - val_accuracy: 0.8736 - val_precision: 0.8868 - val_recall: 0.8559\n",
            "Epoch 47/50\n",
            "106/106 [==============================] - 7s 63ms/step - loss: 0.2350 - accuracy: 0.9297 - precision: 0.9399 - recall: 0.9110 - val_loss: 0.3994 - val_accuracy: 0.8756 - val_precision: 0.8899 - val_recall: 0.8597\n",
            "Epoch 48/50\n",
            "106/106 [==============================] - 7s 67ms/step - loss: 0.2302 - accuracy: 0.9321 - precision: 0.9407 - recall: 0.9144 - val_loss: 0.3984 - val_accuracy: 0.8753 - val_precision: 0.8862 - val_recall: 0.8628\n",
            "Epoch 49/50\n",
            "106/106 [==============================] - 7s 66ms/step - loss: 0.2320 - accuracy: 0.9313 - precision: 0.9397 - recall: 0.9124 - val_loss: 0.4006 - val_accuracy: 0.8753 - val_precision: 0.8862 - val_recall: 0.8628\n",
            "Epoch 50/50\n",
            "106/106 [==============================] - 6s 60ms/step - loss: 0.2240 - accuracy: 0.9360 - precision: 0.9438 - recall: 0.9197 - val_loss: 0.4218 - val_accuracy: 0.8678 - val_precision: 0.8789 - val_recall: 0.8562\n"
          ]
        }
      ],
      "source": [
        "history = model.fit(X_train,y_train,validation_data=(X_val, y_val),batch_size=batch_size,epochs=epochs,verbose=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5b3c1b1a",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T02:04:03.800138Z",
          "iopub.status.busy": "2022-02-03T02:04:03.799376Z",
          "iopub.status.idle": "2022-02-03T02:04:05.860446Z",
          "shell.execute_reply": "2022-02-03T02:04:05.859859Z",
          "shell.execute_reply.started": "2022-02-03T01:51:31.378460Z"
        },
        "papermill": {
          "duration": 3.779017,
          "end_time": "2022-02-03T02:04:05.860595",
          "exception": false,
          "start_time": "2022-02-03T02:04:02.081578",
          "status": "completed"
        },
        "tags": [],
        "id": "5b3c1b1a",
        "outputId": "f4034830-4181-4293-d513-f76a42c5b138"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Accuracy  : 0.8753\n",
            "Precision : 0.8858\n",
            "Recall    : 0.8615\n",
            "F1 Score  : 0.8735\n"
          ]
        }
      ],
      "source": [
        "# Evaluate model on the test set\n",
        "loss, accuracy, precision, recall = model.evaluate(X_test, y_test, verbose=0)\n",
        "# Print metrics\n",
        "print('')\n",
        "print('Accuracy  : {:.4f}'.format(accuracy))\n",
        "print('Precision : {:.4f}'.format(precision))\n",
        "print('Recall    : {:.4f}'.format(recall))\n",
        "print('F1 Score  : {:.4f}'.format(f1_score(precision, recall)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b4184e49",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T02:04:09.367624Z",
          "iopub.status.busy": "2022-02-03T02:04:09.365698Z",
          "iopub.status.idle": "2022-02-03T02:04:09.792662Z",
          "shell.execute_reply": "2022-02-03T02:04:09.791966Z",
          "shell.execute_reply.started": "2022-02-03T01:51:32.960529Z"
        },
        "papermill": {
          "duration": 2.181284,
          "end_time": "2022-02-03T02:04:09.792840",
          "exception": false,
          "start_time": "2022-02-03T02:04:07.611556",
          "status": "completed"
        },
        "tags": [],
        "id": "b4184e49",
        "outputId": "1387363c-d85b-4fe0-9c5c-b770f138d392"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_training_hist(history)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9a458b2d",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2022-02-03T02:04:13.170798Z",
          "iopub.status.busy": "2022-02-03T02:04:13.169630Z",
          "iopub.status.idle": "2022-02-03T02:04:16.869865Z",
          "shell.execute_reply": "2022-02-03T02:04:16.870378Z",
          "shell.execute_reply.started": "2022-02-03T01:51:40.730533Z"
        },
        "papermill": {
          "duration": 5.365676,
          "end_time": "2022-02-03T02:04:16.870552",
          "exception": false,
          "start_time": "2022-02-03T02:04:11.504876",
          "status": "completed"
        },
        "tags": [],
        "id": "9a458b2d",
        "outputId": "17cc6644-d134-4255-fcfb-73dfa7d0f501"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "2    2195\n",
            "1    1833\n",
            "0     456\n",
            "dtype: int64\n",
            "2    2298\n",
            "1    1831\n",
            "0     355\n",
            "dtype: int64\n"
          ]
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_confusion_matrix(model, X_test, y_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "dcbfa1b6",
      "metadata": {
        "papermill": {
          "duration": 1.690699,
          "end_time": "2022-02-03T02:04:20.293980",
          "exception": false,
          "start_time": "2022-02-03T02:04:18.603281",
          "status": "completed"
        },
        "tags": [],
        "id": "dcbfa1b6"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.12"
    },
    "papermill": {
      "default_parameters": {},
      "duration": 654.968736,
      "end_time": "2022-02-03T02:04:24.569634",
      "environment_variables": {},
      "exception": null,
      "input_path": "__notebook__.ipynb",
      "output_path": "__notebook__.ipynb",
      "parameters": {},
      "start_time": "2022-02-03T01:53:29.600898",
      "version": "2.3.3"
    },
    "colab": {
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}