28 실습 - 통계기반 자연어처리 - 토픽모델링 (LDA)

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"28 실습 - 통계기반 자연어처리 - 토픽모델링 (LDA)","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"ATfiKPg2wHkQ"},"source":["# 잠재디리클레할당(LDA, Latent Dirichlet Allocation)"]},{"cell_type":"markdown","metadata":{"id":"62T28EFBhxY2"},"source":["## 환경준비"]},{"cell_type":"code","metadata":{"id":"pX2qNArwVPbY","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1638110444620,"user_tz":-540,"elapsed":3459,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}},"outputId":"ef09c691-cd45-457a-f2ec-a9bf79a3c5c9"},"source":["!pip install pyLDAvis==2.1.2"],"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: pyLDAvis==2.1.2 in /usr/local/lib/python3.7/dist-packages (2.1.2)\n","Requirement already satisfied: wheel>=0.23.0 in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (0.37.0)\n","Requirement already satisfied: future in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (0.16.0)\n","Requirement already satisfied: pytest in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (3.6.4)\n","Requirement already satisfied: numexpr in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (2.7.3)\n","Requirement already satisfied: pandas>=0.17.0 in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (1.1.5)\n","Requirement already satisfied: scipy>=0.18.0 in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (1.4.1)\n","Requirement already satisfied: numpy>=1.9.2 in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (1.19.5)\n","Requirement already satisfied: joblib>=0.8.4 in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (1.1.0)\n","Requirement already satisfied: funcy in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (1.16)\n","Requirement already satisfied: jinja2>=2.7.2 in /usr/local/lib/python3.7/dist-packages (from pyLDAvis==2.1.2) (2.11.3)\n","Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from jinja2>=2.7.2->pyLDAvis==2.1.2) (2.0.1)\n","Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.17.0->pyLDAvis==2.1.2) (2018.9)\n","Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.17.0->pyLDAvis==2.1.2) (2.8.2)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.17.0->pyLDAvis==2.1.2) (1.15.0)\n","Requirement already satisfied: atomicwrites>=1.0 in /usr/local/lib/python3.7/dist-packages (from pytest->pyLDAvis==2.1.2) (1.4.0)\n","Requirement already satisfied: py>=1.5.0 in /usr/local/lib/python3.7/dist-packages (from pytest->pyLDAvis==2.1.2) (1.11.0)\n","Requirement already satisfied: pluggy<0.8,>=0.5 in /usr/local/lib/python3.7/dist-packages (from pytest->pyLDAvis==2.1.2) (0.7.1)\n","Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from pytest->pyLDAvis==2.1.2) (57.4.0)\n","Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.7/dist-packages (from pytest->pyLDAvis==2.1.2) (21.2.0)\n","Requirement already satisfied: more-itertools>=4.0.0 in /usr/local/lib/python3.7/dist-packages (from pytest->pyLDAvis==2.1.2) (8.11.0)\n"]}]},{"cell_type":"code","metadata":{"id":"XSHppaPoqOl2","executionInfo":{"status":"ok","timestamp":1638110451139,"user_tz":-540,"elapsed":461,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}}},"source":["import warnings\n","warnings.filterwarnings(action='ignore')"],"execution_count":10,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"RS7TS1QP9Q7e"},"source":["##1)  sklearn 활용"]},{"cell_type":"code","metadata":{"id":"SaZrFgPaOuqJ","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1638110489197,"user_tz":-540,"elapsed":803,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}},"outputId":"762e3fca-cee6-4e65-9d3c-c995a1d88007"},"source":["import nltk\n","nltk.download('stopwords')\n","from nltk.corpus import stopwords\n","import pandas as pd\n","from sklearn.datasets import fetch_20newsgroups\n","\n","#뉴스 다운로드 및 전처리\n","def get_news(apply_split=True) :\n","  #20newsgroup 다운로드\n","  dataset = fetch_20newsgroups(shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\n","  documents = dataset.data\n","\n","  news_df = pd.DataFrame({'document':documents})\n","  news_df['clean_doc'] = news_df['document'].str.replace(\"[^a-zA-Z]\", \" \") # 특수 문자 제거\n","  news_df['clean_doc'] = news_df['clean_doc'].apply(lambda x: ' '.join([w for w in x.split() if len(w)>3])) # 길이가 3이하인 단어는 제거 (길이가 짧은 단어 제거)\n","  news_df['clean_doc'] = news_df['clean_doc'].apply(lambda x: x.lower())# 전체 단어에 대한 소문자 변환\n","  tokenized_doc = news_df['clean_doc'].apply(lambda x: x.split()) # 토큰화\n","\n","  stop_words = stopwords.words('english') # NLTK 불용어 조회\n","\n","  if apply_split :\n","    return tokenized_doc.apply(lambda x: [item for item in x if item not in stop_words])\n","  else :\n","    return tokenized_doc.apply(lambda x: ' '.join([item for item in x if item not in stop_words]))"],"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["[nltk_data] Downloading package stopwords to /root/nltk_data...\n","[nltk_data]   Package stopwords is already up-to-date!\n"]}]},{"cell_type":"code","metadata":{"id":"cz82Rew1s9kF","executionInfo":{"status":"ok","timestamp":1638110511063,"user_tz":-540,"elapsed":6445,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}}},"source":["#공백으로 토큰 분리\n","def my_tokenizer(text):\n","    return text.split()\n","\n","tokenized_docs = get_news(False)"],"execution_count":12,"outputs":[]},{"cell_type":"code","metadata":{"id":"ZIuciWdLLeuf","executionInfo":{"status":"ok","timestamp":1638110905943,"user_tz":-540,"elapsed":230949,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}}},"source":["from sklearn.feature_extraction.text import TfidfVectorizer\n","from sklearn.decomposition import LatentDirichletAllocation\n","\n","tfidf_vect = TfidfVectorizer(tokenizer=my_tokenizer)\n","tfidf = tfidf_vect.fit_transform(tokenized_docs)\n","lda = LatentDirichletAllocation(n_components=20, max_iter=20, learning_method='online', random_state=0)\n","lda_output = lda.fit_transform(tfidf)"],"execution_count":13,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"RpHv_KHAdtyK"},"source":["\\"]},{"cell_type":"code","metadata":{"id":"oyAE2FJjI1CV","colab":{"base_uri":"https://localhost:8080/","height":882},"executionInfo":{"status":"ok","timestamp":1638111028430,"user_tz":-540,"elapsed":27271,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}},"outputId":"151b1654-4f98-4156-bde9-daeb17cddddd"},"source":["#!pip install pyLDAvis\n","import pyLDAvis\n","import pyLDAvis.sklearn\n","\n","pyLDAvis.enable_notebook()\n","vis = pyLDAvis.sklearn.prepare(lda, tfidf, tfidf_vect, mds='tsne')\n","pyLDAvis.display(vis)\n"],"execution_count":14,"outputs":[{"output_type":"execute_result","data":{"text/html":["\n","<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.css\">\n","\n","\n","<div id=\"ldavis_el611400430562213921429027471\"></div>\n","<script type=\"text/javascript\">\n","\n","var ldavis_el611400430562213921429027471_data = {\"mdsDat\": {\"x\": [-10.878067970275879, -60.88402557373047, -2.3361191749572754, -61.385318756103516, -28.737743377685547, 1.0666056871414185, 45.14072036743164, -140.7959747314453, 61.531681060791016, -72.56305694580078, 15.984491348266602, -160.85162353515625, 85.96183013916016, -99.02083587646484, -176.76412963867188, -117.18988037109375, 108.82991790771484, 47.588096618652344, -106.46783447265625, -50.61380386352539], \"y\": [10.538727760314941, -75.5918197631836, -53.2890739440918, -12.914633750915527, 126.2969970703125, -123.55281066894531, -7.947869300842285, 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\"connect\", \"could\", \"ditto\", \"dortmund\", \"drive\", \"even\", \"fall\", \"fingerprints\", \"first\", \"fluke\", \"garrett\", \"germany\", \"good\", \"gordon\", \"gordon\", \"howell\", \"inherit\", \"intellect\", \"jagr\", \"keller\", \"kingman\", \"kkeller\", \"know\", \"kong\", \"lemieux\", \"like\", \"lives\", \"mail\", \"make\", \"many\", \"migraine\", \"mormon\", \"mormons\", \"much\", \"names\", \"need\", \"nolan\", \"nrhj\", \"owners\", \"part\", \"people\", \"phigs\", \"pitcher\", \"pitt\", \"pitt\", \"please\", \"policy\", \"problem\", \"providence\", \"quakers\", \"range\", \"reality\", \"really\", \"reflective\", \"right\", \"rochester\", \"shameful\", \"shrink\", \"skepticism\", \"skepticism\", \"something\", \"soon\", \"soon\", \"specifically\", \"starting\", \"suck\", \"surrender\", \"surrender\", \"system\", \"thanks\", \"think\", \"tiger\", \"time\", \"traded\", \"traded\", \"upenn\", \"used\", \"viola\", \"viper\", \"volvo\", \"want\", \"well\", \"whoops\", \"windows\", \"work\", \"would\"]}, \"R\": 30, \"lambda.step\": 0.01, \"plot.opts\": {\"xlab\": \"PC1\", \"ylab\": \"PC2\"}, \"topic.order\": [3, 19, 10, 8, 7, 6, 1, 5, 4, 17, 13, 18, 11, 2, 9, 14, 15, 20, 12, 16]};\n","\n","function LDAvis_load_lib(url, callback){\n","  var s = document.createElement('script');\n","  s.src = url;\n","  s.async = true;\n","  s.onreadystatechange = s.onload = callback;\n","  s.onerror = function(){console.warn(\"failed to load library \" + url);};\n","  document.getElementsByTagName(\"head\")[0].appendChild(s);\n","}\n","\n","if(typeof(LDAvis) !== \"undefined\"){\n","   // already loaded: just create the visualization\n","   !function(LDAvis){\n","       new LDAvis(\"#\" + \"ldavis_el611400430562213921429027471\", ldavis_el611400430562213921429027471_data);\n","   }(LDAvis);\n","}else if(typeof define === \"function\" && define.amd){\n","   // require.js is available: use it to load d3/LDAvis\n","   require.config({paths: {d3: \"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min\"}});\n","   require([\"d3\"], function(d3){\n","      window.d3 = d3;\n","      LDAvis_load_lib(\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.js\", function(){\n","        new LDAvis(\"#\" + \"ldavis_el611400430562213921429027471\", ldavis_el611400430562213921429027471_data);\n","      });\n","    });\n","}else{\n","    // require.js not available: dynamically load d3 & LDAvis\n","    LDAvis_load_lib(\"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js\", function(){\n","         LDAvis_load_lib(\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.js\", function(){\n","                 new LDAvis(\"#\" + \"ldavis_el611400430562213921429027471\", ldavis_el611400430562213921429027471_data);\n","            })\n","         });\n","}\n","</script>"],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"execution_count":14}]},{"cell_type":"markdown","metadata":{"id":"xf_J97e1NsTl"},"source":["##2) gensim 활용"]},{"cell_type":"code","metadata":{"id":"r-FAziaL9KJ6","executionInfo":{"status":"ok","timestamp":1638111242555,"user_tz":-540,"elapsed":22191,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}}},"source":["from gensim import corpora\n","from gensim.models import LdaModel, TfidfModel\n","\n","tokenized_docs = get_news()\n","id2word = corpora.Dictionary(tokenized_docs)\n","corpus_TDM = [id2word.doc2bow(d) for d in tokenized_docs]\n","\n","n = 20\n","lda = LdaModel(corpus=corpus_TDM, id2word=id2word, num_topics=n, random_state=0)\n"],"execution_count":15,"outputs":[]},{"cell_type":"code","metadata":{"id":"shGD7kDtDF7_","executionInfo":{"status":"ok","timestamp":1638104895406,"user_tz":-540,"elapsed":1153,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}}},"source":[""],"execution_count":7,"outputs":[]},{"cell_type":"code","metadata":{"id":"42GDOBDWYR0D","colab":{"base_uri":"https://localhost:8080/","height":882},"executionInfo":{"status":"ok","timestamp":1638111337133,"user_tz":-540,"elapsed":28375,"user":{"displayName":"이민호","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiFPPatrtQJJCEfMd6D3DoTVRog9gVm7Ovj5Lex=s64","userId":"15829449822908558555"}},"outputId":"43987a6f-e396-4ff4-f9a6-62603797b563"},"source":["import pyLDAvis\n","import pyLDAvis.gensim \n","\n","pyLDAvis.enable_notebook()\n","vis = pyLDAvis.gensim.prepare(lda, corpus_TDM, id2word, mds='tsne')\n","pyLDAvis.display(vis)\n"],"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/html":["\n","<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.css\">\n","\n","\n","<div id=\"ldavis_el611400426542149927769393870\"></div>\n","<script type=\"text/javascript\">\n","\n","var ldavis_el611400426542149927769393870_data = {\"mdsDat\": {\"x\": [-10.878067970275879, -60.88402557373047, -2.3361191749572754, -61.385318756103516, -28.737743377685547, 1.0666056871414185, 45.14072036743164, -140.7959747314453, 61.531681060791016, -72.56305694580078, 15.984491348266602, -160.85162353515625, 85.96183013916016, -99.02083587646484, -176.76412963867188, -117.18988037109375, 108.82991790771484, 47.588096618652344, -106.46783447265625, -50.61380386352539], \"y\": [10.538727760314941, -75.5918197631836, -53.2890739440918, -12.914633750915527, 126.2969970703125, -123.55281066894531, -7.947869300842285, 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