tesxt_classification_by_using_artificial_neural_network.ipynb

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  "metadata": {
    "colab": {
      "name": "tesxt classification by using artificial neural network.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMHAnr1y6HUW8tbfF7aCBf3",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Durjoy001/Data-Science/blob/main/tesxt_classification_by_using_artificial_neural_network.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y6xx_yhjcQff"
      },
      "source": [
        "import glob\r\n",
        "import pandas as pd\r\n",
        "import numpy as np\r\n",
        "import os"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5fHzH6qBc_u1"
      },
      "source": [
        "from sklearn.naive_bayes import MultinomialNB\r\n",
        "from sklearn.feature_extraction.text import CountVectorizer\r\n",
        "from sklearn.model_selection import train_test_split\r\n",
        "from sklearn.metrics import accuracy_score\r\n",
        "import time\r\n",
        "import re \r\n",
        "\r\n",
        "from sklearn.pipeline import Pipeline\r\n",
        "from sklearn.feature_extraction.text import TfidfTransformer\r\n",
        "from sklearn.metrics import confusion_matrix\r\n",
        "import joblib"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zkso4s48c_yQ",
        "outputId": "6facf207-3f3e-4fad-d3b1-7f2d7ed74d3b"
      },
      "source": [
        "from google.colab import drive\r\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l0QvVq-fc_1X"
      },
      "source": [
        "path = \"/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/*.xlsx\"\r\n",
        "all_file = glob.glob(path)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XkDRRqmXc_4Z",
        "outputId": "98c4dbe6-5f17-40fe-b7cb-14cbc7d532f4"
      },
      "source": [
        "all_file\r\n"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType10.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType1.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType11.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType9.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType3.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType14.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType17.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType16.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType2.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType5.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType4.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType12.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType7.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType20.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType8.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType13.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType19.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType6.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType0.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType18.xlsx',\n",
              " '/content/drive/MyDrive/Colab Notebooks/Assignment 2/songData/songType15.xlsx']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OD1hvI2tc_7n"
      },
      "source": [
        "names = []\r\n",
        "count = []\r\n",
        "clusters = []\r\n",
        "data = []\r\n",
        "\r\n",
        "for each in all_file:\r\n",
        "    temp = pd.read_excel(each)\r\n",
        "    \r\n",
        "    \r\n",
        "    count.append(len(temp))\r\n",
        "    names.append(each.split('/')[1][:-5])\r\n",
        "    clusters.append(temp['songType'])\r\n",
        "    \r\n",
        "    \r\n",
        "    data.append(temp)\r\n",
        "    \r\n",
        "cluster_ids =clusters"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "j7vwqcQsc_-b",
        "outputId": "01ae77bc-8069-481d-d3e0-67f44313a720"
      },
      "source": [
        "data = pd.concat(data)\r\n",
        "data = data.sample(frac = 1)\r\n",
        "\r\n",
        "data"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>lyrics</th>\n",
              "      <th>songType</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>286</th>\n",
              "      <td>1466</td>\n",
              "      <td>হারানো চোখ হারানো মন হারানো গান হারানো সুর হার...</td>\n",
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              "      <td>9</td>\n",
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              "      <td>রিক্সা চালাও রসিক বন্ধু সামনের রাস্তা দিয়া। মু...</td>\n",
              "      <td>10</td>\n",
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              "      <td>1</td>\n",
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              "<p>4108 rows × 3 columns</p>\n",
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            ],
            "text/plain": [
              "     Unnamed: 0                                             lyrics  songType\n",
              "286        1466  হারানো চোখ হারানো মন হারানো গান হারানো সুর হার...        13\n",
              "583        2200  এই উদাসী হাওয়ার পথে পথে মুকুলগুলি ঝরে আমি কুড়ি...        17\n",
              "815        3499  সাগর সঙ্গমে সাঁতার কেঁটেছি কত কখনতো হই নাই ক্ল...         1\n",
              "38         2755  ও..ও..ও.. গরিয়া তুই কোথায়রে ওহো ও হো হো গরিয়া…...         9\n",
              "108         607  তুমি আমার চোখে চেয়ে আশার প্রদীপ জ্বেলেছিলে হাত...        13\n",
              "..          ...                                                ...       ...\n",
              "353        2234  মন মাঝি তোর বৈঠা নে রে আমি আর বাইতে পারলাম না।...         3\n",
              "131        2113  শাওন রাতে যদি স্মরণে আসে মোরে বাহিরে ঝড় বহে নয়...         7\n",
              "142        1283  কোন্‌ পুরাতন প্রাণের টানে           ছুটেছে মন ...        17\n",
              "13         1422  রিক্সা চালাও রসিক বন্ধু সামনের রাস্তা দিয়া। মু...        10\n",
              "409        1732  সব লাল পাথরই তো চুনি হতে পারে না সব প্রেম মিলন...         1\n",
              "\n",
              "[4108 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
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          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0LpvTwY2dABY"
      },
      "source": [
        "stop_words = [ 'হাই', 'ফ্রিকুয়েন্সি', 'কিন্তু', 'অপ্রয়োজনীয়', 'শব্দ' ]"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yd6PVqXRdAEc"
      },
      "source": [
        "data['lyrics'] = data['lyrics'].apply(lambda x: ' '.join([word for word in x.split() if word not in (stop_words)]))"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-gtD1hq6dAHZ"
      },
      "source": [
        "X_train, X_test, y_train, y_test =  train_test_split(data['lyrics'], data['songType'], test_size=0.33, random_state=42 )"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N1vLyXgRdAKf",
        "outputId": "1dba896a-729d-474c-91f0-50518608a3ac"
      },
      "source": [
        "from sklearn.model_selection import ShuffleSplit\r\n",
        "from sklearn.model_selection import cross_val_score\r\n",
        "from sklearn import metrics\r\n",
        "\r\n",
        "total_data_count = len(data)\r\n",
        "per_class_counts = []\r\n",
        "unique_classes = np.unique(data['songType'].values)\r\n",
        "class_count_mean = np.mean(count)\r\n",
        "\r\n",
        "###########################3\r\n",
        "############### classifier setup ################\r\n",
        "\r\n",
        "from sklearn.neural_network import MLPClassifier\r\n",
        "text_clf_svm = Pipeline([\r\n",
        "    \r\n",
        "    ('vect', CountVectorizer(\r\n",
        "                            analyzer=\"word\", \r\n",
        "                            lowercase=False,\r\n",
        "                            token_pattern=\"[\\S]*\",\r\n",
        "                            tokenizer=None,\r\n",
        "                            ngram_range=(1, 3),\r\n",
        "                            preprocessor=None)),                 \r\n",
        "    ('tfidf', TfidfTransformer()),\r\n",
        "    ('clf-svm',MLPClassifier()),\r\n",
        "                                                                        \r\n",
        "])\r\n",
        "classifier = text_clf_svm.fit(list(X_train), list(y_train))\r\n",
        "\r\n",
        "\r\n",
        "cv = ShuffleSplit(n_splits=5, test_size=0.3, random_state=0)\r\n",
        "score = cross_val_score(text_clf_svm, list(X_train), list(y_train), cv=cv)\r\n",
        "\r\n",
        "print(\"Cross Accuracy: %0.2f (+/- %0.2f)\" % (score.mean(), score.std() * 2))\r\n",
        "\r\n",
        "\r\n",
        "predicted = classifier.predict(X_test)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cross Accuracy: 0.53 (+/- 0.02)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7PCqSbWbx3WB",
        "outputId": "a7116e97-63d3-4be0-fa4b-eccd9df8f338"
      },
      "source": [
        "print(\"Cross Accuracy: %0.2f (+/- %0.2f)\" % (score.mean(), score.std() * 2))\r\n",
        "print(metrics.classification_report(y_test, predicted))"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cross Accuracy: 0.53 (+/- 0.02)\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.00      0.00      0.00         6\n",
            "           1       0.45      0.63      0.53       329\n",
            "           2       0.00      0.00      0.00         4\n",
            "           3       0.44      0.60      0.51       232\n",
            "           4       0.00      0.00      0.00         2\n",
            "           5       0.33      0.06      0.10        18\n",
            "           6       0.88      0.22      0.35        32\n",
            "           7       0.78      0.28      0.41        76\n",
            "           8       0.00      0.00      0.00         9\n",
            "           9       0.00      0.00      0.00        23\n",
            "          10       0.33      0.07      0.12        14\n",
            "          11       0.00      0.00      0.00        12\n",
            "          12       0.33      0.02      0.04        47\n",
            "          13       0.56      0.52      0.54       233\n",
            "          14       0.00      0.00      0.00        18\n",
            "          15       1.00      0.75      0.86         4\n",
            "          16       0.00      0.00      0.00         1\n",
            "          17       0.82      0.93      0.87       274\n",
            "          18       0.00      0.00      0.00         3\n",
            "          19       1.00      0.06      0.11        18\n",
            "          20       0.00      0.00      0.00         1\n",
            "\n",
            "    accuracy                           0.56      1356\n",
            "   macro avg       0.33      0.20      0.21      1356\n",
            "weighted avg       0.55      0.56      0.52      1356\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "  _warn_prf(average, modifier, msg_start, len(result))\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S1E5fbhPx3ZO"
      },
      "source": [
        "import pandas as pd\r\n",
        "confusion_matrix = list(metrics.confusion_matrix(y_test, predicted))"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 610
        },
        "id": "PJcK5lDDdANi",
        "outputId": "3c3b7ccf-efeb-4a23-cfdd-f8fd87cd9def"
      },
      "source": [
        "import seaborn as sn\r\n",
        "import pandas as pd\r\n",
        "import matplotlib.pyplot as plt\r\n",
        "array = confusion_matrix\r\n",
        "df_cm = pd.DataFrame(array, index = [i for i in names],\r\n",
        "              columns = [i for i in names])\r\n",
        "df_norm_col=(df_cm-df_cm.mean())/df_cm.std()\r\n",
        "#df_norm_col=df_cm-df_cm.mean()\r\n",
        "plt.figure(figsize = (15,10))\r\n",
        "sn.heatmap(df_norm_col, annot=True,cmap='viridis')"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa2858e36d8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IK2DaRKPdAQQ"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}