CounterFitBills.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "toc_visible": true,
      "mount_file_id": "1d-L88HcjDK5_GcJUSE_8Aaw8H-WmYYZD",
      "authorship_tag": "ABX9TyNWXvVxyWdonHA5uf5jLkI0",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/velickovski/colaboratoryProjects/blob/main/CounterFitBills.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "mk-0YbVQbx1c",
        "outputId": "5fb48cf5-a9b5-4faa-d7dd-c15a2f01ddfc"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.preprocessing import LabelEncoder, OneHotEncoder, MinMaxScaler\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import classification_report, confusion_matrix, f1_score\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.experimental import enable_iterative_imputer\n",
        "from sklearn.impute import IterativeImputer\n",
        "\n",
        "df = pd.read_csv('/content/sample_data/fake_bills.csv', sep=';')\n",
        "\n",
        "plt.plot(df['is_genuine'])\n",
        "plt.show()\n",
        "df['is_genuine'].value_counts()\n",
        "label_encoder = LabelEncoder()\n",
        "df['is_genuine'] = label_encoder.fit_transform(df['is_genuine'])\n",
        "\n",
        "imputer = IterativeImputer()\n",
        "df[['diagonal', 'height_left','height_right','margin_low','margin_up','length']] = imputer.fit_transform(df[['diagonal', 'height_left','height_right','margin_low','margin_up','length']])\n",
        "\n",
        "\n",
        "X = df.drop(columns=['is_genuine'])\n",
        "Y = df['is_genuine']\n",
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)\n",
        "\n",
        "knn = KNeighborsClassifier(n_neighbors=3)\n",
        "knn.fit(X_train, Y_train)\n",
        "Y_pred = knn.predict(X_test)\n",
        "sns.heatmap(confusion_matrix(Y_test, Y_pred), annot=True, fmt='5.2f')\n",
        "plt.xlabel('Fake')\n",
        "plt.ylabel('Genuine')\n",
        "plt.show()\n",
        "scores = []\n",
        "for k in range(1, 199):\n",
        "    knn = KNeighborsClassifier(n_neighbors=k)\n",
        "    knn.fit(X_train, Y_train)\n",
        "    preds = knn.predict(X_test)\n",
        "    sc = f1_score(preds, Y_test)\n",
        "    scores.append(sc)\n",
        "\n",
        "plt.plot(np.arange(1, 199), scores)\n",
        "plt.show()\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "doh-53tfnUG8"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}