Deep_Learning_approach_ROC_curve.ipynb

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      "name": "Deep-Learning-approach-ROC-curve.ipynb",
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    {
      "cell_type": "code",
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        "execution": {
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          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "from numpy import array\n",
        "from keras.preprocessing.text import one_hot\n",
        "from keras.preprocessing.sequence import pad_sequences\n",
        "from keras.models import Sequential\n",
        "from keras.layers.core import Activation, Dropout, Dense\n",
        "from keras.layers import Flatten, LSTM\n",
        "from keras.layers import GlobalMaxPooling1D\n",
        "from keras.models import Model\n",
        "from keras.layers.embeddings import Embedding\n",
        "from sklearn.model_selection import train_test_split\n",
        "from keras.preprocessing.text import Tokenizer\n",
        "from keras.layers import Input\n",
        "from keras.layers.merge import Concatenate\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import re\n",
        "\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
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          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "toxic_comments = pd.read_csv(\"../input/nlp-coursework/1613373921-5e748a2d5fc288e9f69c5f86.csv\")"
      ],
      "execution_count": null,
      "outputs": []
    },
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      "cell_type": "code",
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        },
        "tags": [],
        "outputId": "1fd14e2d-0933-4675-da32-aa2ff2b16d9a"
      },
      "source": [
        "print(toxic_comments.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(159571, 8)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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        },
        "tags": []
      },
      "source": [
        "label_cols = ['toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
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        "tags": [],
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      },
      "source": [
        "toxic_comments['none'] = 1-toxic_comments[label_cols].max(axis=1)\n",
        "toxic_comments.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>toxic</th>\n",
              "      <th>severe_toxic</th>\n",
              "      <th>obscene</th>\n",
              "      <th>threat</th>\n",
              "      <th>insult</th>\n",
              "      <th>identity_hate</th>\n",
              "      <th>none</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>159571.000000</td>\n",
              "      <td>159571.000000</td>\n",
              "      <td>159571.000000</td>\n",
              "      <td>159571.000000</td>\n",
              "      <td>159571.000000</td>\n",
              "      <td>159571.000000</td>\n",
              "      <td>159571.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.095844</td>\n",
              "      <td>0.009996</td>\n",
              "      <td>0.052948</td>\n",
              "      <td>0.002996</td>\n",
              "      <td>0.049364</td>\n",
              "      <td>0.008805</td>\n",
              "      <td>0.898321</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.294379</td>\n",
              "      <td>0.099477</td>\n",
              "      <td>0.223931</td>\n",
              "      <td>0.054650</td>\n",
              "      <td>0.216627</td>\n",
              "      <td>0.093420</td>\n",
              "      <td>0.302226</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
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              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
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              "    <tr>\n",
              "      <th>75%</th>\n",
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              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ],
            "text/plain": [
              "               toxic   severe_toxic        obscene         threat  \\\n",
              "count  159571.000000  159571.000000  159571.000000  159571.000000   \n",
              "mean        0.095844       0.009996       0.052948       0.002996   \n",
              "std         0.294379       0.099477       0.223931       0.054650   \n",
              "min         0.000000       0.000000       0.000000       0.000000   \n",
              "25%         0.000000       0.000000       0.000000       0.000000   \n",
              "50%         0.000000       0.000000       0.000000       0.000000   \n",
              "75%         0.000000       0.000000       0.000000       0.000000   \n",
              "max         1.000000       1.000000       1.000000       1.000000   \n",
              "\n",
              "              insult  identity_hate           none  \n",
              "count  159571.000000  159571.000000  159571.000000  \n",
              "mean        0.049364       0.008805       0.898321  \n",
              "std         0.216627       0.093420       0.302226  \n",
              "min         0.000000       0.000000       0.000000  \n",
              "25%         0.000000       0.000000       1.000000  \n",
              "50%         0.000000       0.000000       1.000000  \n",
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            "tags": []
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          "execution_count": 5
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        },
        "tags": [],
        "outputId": "68c118e6-5804-40d2-934d-bb090f8afb4d"
      },
      "source": [
        "toxic_comments.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>comment_text</th>\n",
              "      <th>toxic</th>\n",
              "      <th>severe_toxic</th>\n",
              "      <th>obscene</th>\n",
              "      <th>threat</th>\n",
              "      <th>insult</th>\n",
              "      <th>identity_hate</th>\n",
              "      <th>none</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0000997932d777bf</td>\n",
              "      <td>Explanation\\nWhy the edits made under my usern...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>000103f0d9cfb60f</td>\n",
              "      <td>D'aww! He matches this background colour I'm s...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>000113f07ec002fd</td>\n",
              "      <td>Hey man, I'm really not trying to edit war. It...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0001b41b1c6bb37e</td>\n",
              "      <td>\"\\nMore\\nI can't make any real suggestions on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0001d958c54c6e35</td>\n",
              "      <td>You, sir, are my hero. Any chance you remember...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id                                       comment_text  toxic  \\\n",
              "0  0000997932d777bf  Explanation\\nWhy the edits made under my usern...      0   \n",
              "1  000103f0d9cfb60f  D'aww! He matches this background colour I'm s...      0   \n",
              "2  000113f07ec002fd  Hey man, I'm really not trying to edit war. It...      0   \n",
              "3  0001b41b1c6bb37e  \"\\nMore\\nI can't make any real suggestions on ...      0   \n",
              "4  0001d958c54c6e35  You, sir, are my hero. Any chance you remember...      0   \n",
              "\n",
              "   severe_toxic  obscene  threat  insult  identity_hate  none  \n",
              "0             0        0       0       0              0     1  \n",
              "1             0        0       0       0              0     1  \n",
              "2             0        0       0       0              0     1  \n",
              "3             0        0       0       0              0     1  \n",
              "4             0        0       0       0              0     1  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
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          "start_time": "2021-03-01T15:12:25.075030",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "filter = toxic_comments[\"comment_text\"] != \"\"\n",
        "toxic_comments = toxic_comments[filter]\n",
        "toxic_comments = toxic_comments.dropna()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:12:25.260196Z",
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        },
        "tags": [],
        "outputId": "94f58db0-adb0-4dfa-bad5-11c180cbdedb"
      },
      "source": [
        "print(toxic_comments[\"comment_text\"][168])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "You should be fired, you're a moronic wimp who is too lazy to do research. It makes me sick that people like you exist in this world.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
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        },
        "tags": [],
        "outputId": "206fd5ff-7f6d-4af3-a82b-da037bafa0dc"
      },
      "source": [
        "print(\"Toxic:\" + str(toxic_comments[\"toxic\"][168]))\n",
        "print(\"Severe_toxic:\" + str(toxic_comments[\"severe_toxic\"][168]))\n",
        "print(\"Obscene:\" + str(toxic_comments[\"obscene\"][168]))\n",
        "print(\"Threat:\" + str(toxic_comments[\"threat\"][168]))\n",
        "print(\"Insult:\" + str(toxic_comments[\"insult\"][168]))\n",
        "print(\"Identity_hate:\" + str(toxic_comments[\"identity_hate\"][168]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Toxic:1\n",
            "Severe_toxic:0\n",
            "Obscene:0\n",
            "Threat:0\n",
            "Insult:1\n",
            "Identity_hate:0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:12:25.390033Z",
          "iopub.status.busy": "2021-03-01T15:12:25.388855Z",
          "iopub.status.idle": "2021-03-01T15:12:25.393384Z",
          "shell.execute_reply": "2021-03-01T15:12:25.393891Z"
        },
        "id": "M9em5yOBzAk4",
        "papermill": {
          "duration": 0.044258,
          "end_time": "2021-03-01T15:12:25.394075",
          "exception": false,
          "start_time": "2021-03-01T15:12:25.349817",
          "status": "completed"
        },
        "tags": [],
        "outputId": "0c27e86e-2453-4ef2-92fb-d5d67464f5c7"
      },
      "source": [
        "toxic_comments_labels = toxic_comments[[\"toxic\", \"severe_toxic\", \"obscene\", \"threat\", \"insult\", \"identity_hate\",\"none\"]]\n",
        "toxic_comments_labels.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>toxic</th>\n",
              "      <th>severe_toxic</th>\n",
              "      <th>obscene</th>\n",
              "      <th>threat</th>\n",
              "      <th>insult</th>\n",
              "      <th>identity_hate</th>\n",
              "      <th>none</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   toxic  severe_toxic  obscene  threat  insult  identity_hate  none\n",
              "0      0             0        0       0       0              0     1\n",
              "1      0             0        0       0       0              0     1\n",
              "2      0             0        0       0       0              0     1\n",
              "3      0             0        0       0       0              0     1\n",
              "4      0             0        0       0       0              0     1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:12:25.447790Z",
          "iopub.status.busy": "2021-03-01T15:12:25.446937Z",
          "iopub.status.idle": "2021-03-01T15:12:25.697566Z",
          "shell.execute_reply": "2021-03-01T15:12:25.698075Z"
        },
        "id": "mhYKFKgYzAk4",
        "papermill": {
          "duration": 0.280824,
          "end_time": "2021-03-01T15:12:25.698284",
          "exception": false,
          "start_time": "2021-03-01T15:12:25.417460",
          "status": "completed"
        },
        "tags": [],
        "outputId": "156a8845-143a-4035-d2a4-0eca3d3cb7df"
      },
      "source": [
        "fig_size = plt.rcParams[\"figure.figsize\"]\n",
        "fig_size[0] = 10\n",
        "fig_size[1] = 8\n",
        "plt.rcParams[\"figure.figsize\"] = fig_size\n",
        "\n",
        "toxic_comments_labels.sum(axis=0).plot.bar()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:12:25.756253Z",
          "iopub.status.busy": "2021-03-01T15:12:25.754631Z",
          "iopub.status.idle": "2021-03-01T15:12:25.757003Z",
          "shell.execute_reply": "2021-03-01T15:12:25.757565Z"
        },
        "id": "p9kuXhEBzAk5",
        "papermill": {
          "duration": 0.034373,
          "end_time": "2021-03-01T15:12:25.757745",
          "exception": false,
          "start_time": "2021-03-01T15:12:25.723372",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "def preprocess_text(sen):\n",
        "    # Remove punctuations and numbers\n",
        "    sentence = re.sub('[^a-zA-Z]', ' ', sen)\n",
        "\n",
        "    # Single character removal\n",
        "    sentence = re.sub(r\"\\s+[a-zA-Z]\\s+\", ' ', sentence)\n",
        "\n",
        "    # Removing multiple spaces\n",
        "    sentence = re.sub(r'\\s+', ' ', sentence)\n",
        "\n",
        "    return sentence"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:12:25.878973Z",
          "iopub.status.busy": "2021-03-01T15:12:25.848128Z",
          "iopub.status.idle": "2021-03-01T15:12:46.222648Z",
          "shell.execute_reply": "2021-03-01T15:12:46.221865Z"
        },
        "id": "-a77oiU8zAk5",
        "papermill": {
          "duration": 20.440049,
          "end_time": "2021-03-01T15:12:46.222820",
          "exception": false,
          "start_time": "2021-03-01T15:12:25.782771",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "X = []\n",
        "sentences = list(toxic_comments[\"comment_text\"])\n",
        "for sen in sentences:\n",
        "    X.append(preprocess_text(sen))\n",
        "\n",
        "y = toxic_comments_labels.values"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:12:46.280137Z",
          "iopub.status.busy": "2021-03-01T15:12:46.279224Z",
          "iopub.status.idle": "2021-03-01T15:12:46.368811Z",
          "shell.execute_reply": "2021-03-01T15:12:46.368199Z"
        },
        "id": "WVHIkusWzAk5",
        "papermill": {
          "duration": 0.120512,
          "end_time": "2021-03-01T15:12:46.368977",
          "exception": false,
          "start_time": "2021-03-01T15:12:46.248465",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:12:46.448824Z",
          "iopub.status.busy": "2021-03-01T15:12:46.443799Z",
          "iopub.status.idle": "2021-03-01T15:13:09.693657Z",
          "shell.execute_reply": "2021-03-01T15:13:09.692505Z"
        },
        "id": "ANSgyddlzAk5",
        "papermill": {
          "duration": 23.299493,
          "end_time": "2021-03-01T15:13:09.693841",
          "exception": false,
          "start_time": "2021-03-01T15:12:46.394348",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "tokenizer = Tokenizer(num_words=5000)\n",
        "tokenizer.fit_on_texts(X_train)\n",
        "\n",
        "X_train = tokenizer.texts_to_sequences(X_train)\n",
        "X_test = tokenizer.texts_to_sequences(X_test)\n",
        "\n",
        "vocab_size = len(tokenizer.word_index) + 1\n",
        "\n",
        "maxlen = 200\n",
        "\n",
        "X_train = pad_sequences(X_train, padding='post', maxlen=maxlen)\n",
        "X_test = pad_sequences(X_test, padding='post', maxlen=maxlen)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:13:09.753918Z",
          "iopub.status.busy": "2021-03-01T15:13:09.753088Z",
          "iopub.status.idle": "2021-03-01T15:13:31.627950Z",
          "shell.execute_reply": "2021-03-01T15:13:31.626718Z"
        },
        "id": "CD5azJZ1zAk6",
        "papermill": {
          "duration": 21.908436,
          "end_time": "2021-03-01T15:13:31.628122",
          "exception": false,
          "start_time": "2021-03-01T15:13:09.719686",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "from numpy import array\n",
        "from numpy import asarray\n",
        "from numpy import zeros\n",
        "\n",
        "embeddings_dictionary = dict()\n",
        "\n",
        "glove_file = open('../input/glove-global-vectors-for-word-representation/glove.6B.100d.txt', encoding=\"utf8\")\n",
        "\n",
        "for line in glove_file:\n",
        "    records = line.split()\n",
        "    word = records[0]\n",
        "    vector_dimensions = asarray(records[1:], dtype='float32')\n",
        "    embeddings_dictionary[word] = vector_dimensions\n",
        "glove_file.close()\n",
        "\n",
        "embedding_matrix = zeros((vocab_size, 100))\n",
        "for word, index in tokenizer.word_index.items():\n",
        "    embedding_vector = embeddings_dictionary.get(word)\n",
        "    if embedding_vector is not None:\n",
        "        embedding_matrix[index] = embedding_vector"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:13:31.687177Z",
          "iopub.status.busy": "2021-03-01T15:13:31.686429Z",
          "iopub.status.idle": "2021-03-01T15:13:35.952430Z",
          "shell.execute_reply": "2021-03-01T15:13:35.951801Z"
        },
        "id": "Nf90rm0JzAk6",
        "papermill": {
          "duration": 4.298584,
          "end_time": "2021-03-01T15:13:35.952596",
          "exception": false,
          "start_time": "2021-03-01T15:13:31.654012",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "deep_inputs = Input(shape=(maxlen,))\n",
        "embedding_layer = Embedding(vocab_size, 100, weights=[embedding_matrix], trainable=False)(deep_inputs)\n",
        "LSTM_Layer_1 = LSTM(128)(embedding_layer)\n",
        "dense_layer_1 = Dense(7, activation='sigmoid')(LSTM_Layer_1)\n",
        "model = Model(inputs=deep_inputs, outputs=dense_layer_1)\n",
        "\n",
        "model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['acc'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:13:36.018128Z",
          "iopub.status.busy": "2021-03-01T15:13:36.017208Z",
          "iopub.status.idle": "2021-03-01T15:13:36.021517Z",
          "shell.execute_reply": "2021-03-01T15:13:36.018832Z"
        },
        "id": "MPGYHWDIzAk6",
        "papermill": {
          "duration": 0.042657,
          "end_time": "2021-03-01T15:13:36.021711",
          "exception": false,
          "start_time": "2021-03-01T15:13:35.979054",
          "status": "completed"
        },
        "tags": [],
        "outputId": "e070d05f-676e-4b5b-e6cc-0bc5864dbbc1"
      },
      "source": [
        "print(model.summary())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_1 (InputLayer)         [(None, 200)]             0         \n",
            "_________________________________________________________________\n",
            "embedding (Embedding)        (None, 200, 100)          14824300  \n",
            "_________________________________________________________________\n",
            "lstm (LSTM)                  (None, 128)               117248    \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 7)                 903       \n",
            "=================================================================\n",
            "Total params: 14,942,451\n",
            "Trainable params: 118,151\n",
            "Non-trainable params: 14,824,300\n",
            "_________________________________________________________________\n",
            "None\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:13:36.082486Z",
          "iopub.status.busy": "2021-03-01T15:13:36.081512Z",
          "iopub.status.idle": "2021-03-01T15:13:36.808434Z",
          "shell.execute_reply": "2021-03-01T15:13:36.807818Z"
        },
        "id": "Z35bb68RzAk6",
        "papermill": {
          "duration": 0.759404,
          "end_time": "2021-03-01T15:13:36.808596",
          "exception": false,
          "start_time": "2021-03-01T15:13:36.049192",
          "status": "completed"
        },
        "tags": [],
        "outputId": "265e541e-7f10-420a-813d-e6c60e04bb44"
      },
      "source": [
        "from keras.utils import plot_model\n",
        "plot_model(model, to_file='model_plot4a.png', show_shapes=True, show_layer_names=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:13:36.872967Z",
          "iopub.status.busy": "2021-03-01T15:13:36.872168Z",
          "iopub.status.idle": "2021-03-01T15:16:38.461587Z",
          "shell.execute_reply": "2021-03-01T15:16:38.460832Z"
        },
        "id": "d2q1kVKdzAk7",
        "papermill": {
          "duration": 181.624479,
          "end_time": "2021-03-01T15:16:38.461768",
          "exception": false,
          "start_time": "2021-03-01T15:13:36.837289",
          "status": "completed"
        },
        "tags": [],
        "outputId": "f7234f84-ac06-41d8-a15a-a612d7a7e205"
      },
      "source": [
        "history = model.fit(X_train, y_train, batch_size=128, epochs=10, verbose=1, validation_split=0.2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "798/798 [==============================] - 23s 23ms/step - loss: 0.2030 - acc: 0.8919 - val_loss: 0.1694 - val_acc: 0.8991\n",
            "Epoch 2/10\n",
            "798/798 [==============================] - 18s 22ms/step - loss: 0.1087 - acc: 0.9232 - val_loss: 0.0734 - val_acc: 0.9479\n",
            "Epoch 3/10\n",
            "798/798 [==============================] - 17s 22ms/step - loss: 0.0708 - acc: 0.9483 - val_loss: 0.0731 - val_acc: 0.9488\n",
            "Epoch 4/10\n",
            "798/798 [==============================] - 18s 22ms/step - loss: 0.0677 - acc: 0.9520 - val_loss: 0.0665 - val_acc: 0.9526\n",
            "Epoch 5/10\n",
            "798/798 [==============================] - 17s 22ms/step - loss: 0.0645 - acc: 0.9536 - val_loss: 0.0667 - val_acc: 0.9540\n",
            "Epoch 6/10\n",
            "798/798 [==============================] - 18s 22ms/step - loss: 0.0625 - acc: 0.9559 - val_loss: 0.0637 - val_acc: 0.9554\n",
            "Epoch 7/10\n",
            "798/798 [==============================] - 17s 22ms/step - loss: 0.0595 - acc: 0.9580 - val_loss: 0.0658 - val_acc: 0.9548\n",
            "Epoch 8/10\n",
            "798/798 [==============================] - 18s 22ms/step - loss: 0.0568 - acc: 0.9595 - val_loss: 0.0629 - val_acc: 0.9577\n",
            "Epoch 9/10\n",
            "798/798 [==============================] - 18s 22ms/step - loss: 0.0573 - acc: 0.9591 - val_loss: 0.0616 - val_acc: 0.9572\n",
            "Epoch 10/10\n",
            "798/798 [==============================] - 17s 22ms/step - loss: 0.0532 - acc: 0.9628 - val_loss: 0.0621 - val_acc: 0.9572\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:16:40.651482Z",
          "iopub.status.busy": "2021-03-01T15:16:40.650357Z",
          "iopub.status.idle": "2021-03-01T15:16:46.768127Z",
          "shell.execute_reply": "2021-03-01T15:16:46.768921Z"
        },
        "id": "YVSpNFswzAk7",
        "papermill": {
          "duration": 7.261226,
          "end_time": "2021-03-01T15:16:46.769183",
          "exception": false,
          "start_time": "2021-03-01T15:16:39.507957",
          "status": "completed"
        },
        "tags": [],
        "outputId": "7cf05bd2-2f48-4cf5-bdae-d56262076dd7"
      },
      "source": [
        "score = model.evaluate(X_test, y_test, verbose=1)\n",
        "\n",
        "print(\"Test Score:\", score[0])\n",
        "print(\"Test Accuracy:\", score[1])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "998/998 [==============================] - 6s 6ms/step - loss: 0.0605 - acc: 0.9578\n",
            "Test Score: 0.06051557883620262\n",
            "Test Accuracy: 0.9577941298484802\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:16:49.017464Z",
          "iopub.status.busy": "2021-03-01T15:16:49.016083Z",
          "iopub.status.idle": "2021-03-01T15:16:49.429896Z",
          "shell.execute_reply": "2021-03-01T15:16:49.429130Z"
        },
        "id": "pGjaA_HMzAk7",
        "papermill": {
          "duration": 1.571008,
          "end_time": "2021-03-01T15:16:49.430067",
          "exception": false,
          "start_time": "2021-03-01T15:16:47.859059",
          "status": "completed"
        },
        "tags": [],
        "outputId": "07dcbe09-a41e-4dfe-c38c-1ccacb1ef1db"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.plot(history.history['acc'])\n",
        "plt.plot(history.history['val_acc'])\n",
        "\n",
        "plt.title('model accuracy')\n",
        "plt.ylabel('accuracy')\n",
        "plt.xlabel('epoch')\n",
        "plt.legend(['train','test'], loc='upper left')\n",
        "plt.show()\n",
        "\n",
        "plt.plot(history.history['loss'])\n",
        "plt.plot(history.history['val_loss'])\n",
        "\n",
        "plt.title('model loss')\n",
        "plt.ylabel('loss')\n",
        "plt.xlabel('epoch')\n",
        "plt.legend(['train','test'], loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:16:51.896052Z",
          "iopub.status.busy": "2021-03-01T15:16:51.895002Z",
          "iopub.status.idle": "2021-03-01T15:16:57.158838Z",
          "shell.execute_reply": "2021-03-01T15:16:57.159808Z"
        },
        "id": "v_TlAouQzAk7",
        "papermill": {
          "duration": 6.623395,
          "end_time": "2021-03-01T15:16:57.160029",
          "exception": false,
          "start_time": "2021-03-01T15:16:50.536634",
          "status": "completed"
        },
        "tags": [],
        "outputId": "823ba74a-b81d-4c79-944d-99d4a2a3d286"
      },
      "source": [
        "snn_pred = model.predict(X_test)\n",
        "print(snn_pred)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[5.5422340e-02 2.9687129e-04 1.0016535e-02 ... 1.0422238e-02\n",
            "  2.8573244e-03 9.4150054e-01]\n",
            " [4.6366465e-04 2.0619054e-06 1.4465617e-04 ... 9.1397895e-05\n",
            "  2.6702788e-05 9.9936920e-01]\n",
            " [6.8536084e-03 3.6019028e-05 1.3565832e-03 ... 1.3368475e-03\n",
            "  3.9512725e-04 9.9256235e-01]\n",
            " ...\n",
            " [3.8518438e-03 1.5580823e-05 8.4967661e-04 ... 6.8622536e-04\n",
            "  2.1153834e-04 9.9560863e-01]\n",
            " [9.1474611e-01 3.5623953e-02 5.2920592e-01 ... 5.0931227e-01\n",
            "  9.9752136e-02 4.3065414e-02]\n",
            " [1.6900878e-03 7.9667052e-06 4.4877053e-04 ... 3.4616052e-04\n",
            "  1.1454421e-04 9.9746728e-01]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-03-01T15:16:59.459434Z",
          "iopub.status.busy": "2021-03-01T15:16:59.454563Z",
          "iopub.status.idle": "2021-03-01T15:17:00.358045Z",
          "shell.execute_reply": "2021-03-01T15:17:00.358632Z"
        },
        "id": "Lj_4JBiYzAk7",
        "papermill": {
          "duration": 2.013878,
          "end_time": "2021-03-01T15:17:00.358831",
          "exception": false,
          "start_time": "2021-03-01T15:16:58.344953",
          "status": "completed"
        },
        "tags": [],
        "outputId": "2a3b319d-9842-4dd3-f451-b0810fb04c02"
      },
      "source": [
        "from sklearn.datasets import make_classification\n",
        "from sklearn.preprocessing import label_binarize\n",
        "from scipy import interp\n",
        "from itertools import cycle\n",
        "\n",
        "n_classes = 7\n",
        "\n",
        "from sklearn.metrics import roc_curve, auc\n",
        "\n",
        "# Plot linewidth.\n",
        "lw = 2\n",
        "\n",
        "# Compute ROC curve and ROC area for each class\n",
        "fpr = dict()\n",
        "tpr = dict()\n",
        "roc_auc = dict()\n",
        "for i in range(n_classes):\n",
        "    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], snn_pred[:, i])\n",
        "    roc_auc[i] = auc(fpr[i], tpr[i])\n",
        "\n",
        "# Compute micro-average ROC curve and ROC area\n",
        "fpr[\"micro\"], tpr[\"micro\"], _ = roc_curve(y_test.ravel(), snn_pred.ravel())\n",
        "roc_auc[\"micro\"] = auc(fpr[\"micro\"], tpr[\"micro\"])\n",
        "\n",
        "# Compute macro-average ROC curve and ROC area\n",
        "\n",
        "# First aggregate all false positive rates\n",
        "all_fpr = np.unique(np.concatenate([fpr[i] for i in range(n_classes)]))\n",
        "\n",
        "# Then interpolate all ROC curves at this points\n",
        "mean_tpr = np.zeros_like(all_fpr)\n",
        "for i in range(n_classes):\n",
        "    mean_tpr += interp(all_fpr, fpr[i], tpr[i])\n",
        "\n",
        "# Finally average it and compute AUC\n",
        "mean_tpr /= n_classes\n",
        "\n",
        "fpr[\"macro\"] = all_fpr\n",
        "tpr[\"macro\"] = mean_tpr\n",
        "roc_auc[\"macro\"] = auc(fpr[\"macro\"], tpr[\"macro\"])\n",
        "\n",
        "# Plot all ROC curves\n",
        "plt.figure(1)\n",
        "plt.plot(fpr[\"micro\"], tpr[\"micro\"],\n",
        "         label='micro-average ROC curve (area = {0:0.5f})'\n",
        "               ''.format(roc_auc[\"micro\"]),\n",
        "         color='deeppink', linestyle=':', linewidth=4)\n",
        "\n",
        "plt.plot(fpr[\"macro\"], tpr[\"macro\"],\n",
        "         label='macro-average ROC curve (area = {0:0.5f})'\n",
        "               ''.format(roc_auc[\"macro\"]),\n",
        "         color='navy', linestyle=':', linewidth=4)\n",
        "\n",
        "colors = cycle(['aqua', 'darkorange', 'cornflowerblue'])\n",
        "for i, color in zip(range(n_classes), colors):\n",
        "    plt.plot(fpr[i], tpr[i], color=color, lw=lw,\n",
        "             label='ROC curve of class {0} (area = {1:0.5f})'\n",
        "             ''.format(i, roc_auc[i]))\n",
        "\n",
        "plt.plot([0, 1], [0, 1], 'k--', lw=lw)\n",
        "plt.xlim([0.0, 1.0])\n",
        "plt.ylim([0.0, 1.05])\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.title('Some extension of Receiver operating characteristic to multi-class')\n",
        "plt.legend(loc=\"lower right\")\n",
        "plt.show()\n",
        "\n",
        "\n",
        "# Zoom in view of the upper left corner.\n",
        "plt.figure(2)\n",
        "plt.xlim(0, 0.2)\n",
        "plt.ylim(0.8, 1)\n",
        "plt.plot(fpr[\"micro\"], tpr[\"micro\"],\n",
        "         label='micro-average ROC curve (area = {0:0.5f})'\n",
        "               ''.format(roc_auc[\"micro\"]),\n",
        "         color='deeppink', linestyle=':', linewidth=4)\n",
        "\n",
        "plt.plot(fpr[\"macro\"], tpr[\"macro\"],\n",
        "         label='macro-average ROC curve (area = {0:0.5f})'\n",
        "               ''.format(roc_auc[\"macro\"]),\n",
        "         color='navy', linestyle=':', linewidth=4)\n",
        "\n",
        "colors = cycle(['aqua', 'darkorange', 'cornflowerblue'])\n",
        "for i, color in zip(range(7), colors):\n",
        "    plt.plot(fpr[i], tpr[i], color=color, lw=lw,\n",
        "             label='ROC curve of class {0} (area = {1:0.5f})'\n",
        "             ''.format(i, roc_auc[i]))\n",
        "\n",
        "plt.plot([0, 1], [0, 1], 'k--', lw=lw)\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.title('Some extension of Receiver operating characteristic to multi-class')\n",
        "plt.legend(loc=\"lower right\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:33: DeprecationWarning: scipy.interp is deprecated and will be removed in SciPy 2.0.0, use numpy.interp instead\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sgioGaMxzmU8",
        "papermill": {
          "duration": 1.181312,
          "end_time": "2021-03-01T15:17:02.636257",
          "exception": false,
          "start_time": "2021-03-01T15:17:01.454945",
          "status": "completed"
        },
        "tags": []
      },
      "source": [
        "* class 0:\"toxic\"\n",
        "* class 1:\"severe_toxic\"\n",
        "* class 2:\"obscene\"\n",
        "* class 3:\"threat\"\n",
        "* class 4:\"insult\"\n",
        "* class 5:\"identity_hate\"\n",
        "* class 6:\"non_toxic\""
      ]
    }
  ]
}