multi_modal_clicks.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "IfQyr2Qmg7Qk"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "xa_AfCEsg7Qm"
      },
      "outputs": [],
      "source": [
        "df = pd.read_csv('datasets/Train.csv')\n",
        "\n",
        "# ignore columns call_type\tcall_status\tstart_time\tduration\tend_time\tdisplay_location\n",
        "\n",
        "df = df.drop(columns=['call_type', 'call_status', 'start_time', 'duration', 'end_time', 'display_location'])\n",
        "df['conversions_calls'] = df['conversions_calls'].interpolate().fillna(df['conversions_calls'].interpolate().mean())\n",
        "\n",
        "\n",
        "# Step 1: Identify numeric columns\n",
        "numeric_columns = df.select_dtypes(include=['float64']).columns\n",
        "df[numeric_columns] = df[numeric_columns].fillna(df[numeric_columns].mean())\n",
        "df = df.dropna()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rssXBvzlp-5y",
        "outputId": "38ec5f52-f96b-4946-ca16-0b4796dc742d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 289526 entries, 0 to 289525\n",
            "Data columns (total 13 columns):\n",
            " #   Column              Non-Null Count   Dtype  \n",
            "---  ------              --------------   -----  \n",
            " 0   impressions         289526 non-null  float64\n",
            " 1   clicks              289526 non-null  float64\n",
            " 2   cost                289526 non-null  float64\n",
            " 3   conversions         289526 non-null  float64\n",
            " 4   ad_type             289526 non-null  object \n",
            " 5   currency            289526 non-null  object \n",
            " 6   ID                  289526 non-null  object \n",
            " 7   date                289526 non-null  object \n",
            " 8   impression_share    289526 non-null  float64\n",
            " 9   conversions_calls   289526 non-null  float64\n",
            " 10  headline1_len       289526 non-null  float64\n",
            " 11  headline2_len       289526 non-null  float64\n",
            " 12  ad_description_len  289526 non-null  float64\n",
            "dtypes: float64(9), object(4)\n",
            "memory usage: 30.9+ MB\n"
          ]
        }
      ],
      "source": [
        "df.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9XyR2AjslIRm",
        "outputId": "80c5abb6-2a36-4a5c-ebab-17088ab2a6f3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(array(['ZAR', 'USD'], dtype=object), 2)"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df['currency'].unique(), df['currency'].nunique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "2B2lME-TlIRn"
      },
      "outputs": [],
      "source": [
        "# Example exchange rates for ZAR and USD\n",
        "exchange_rates = {'USD': 1.0, 'ZAR': 0.071}  # 1 USD = 0.071 ZAR\n",
        "\n",
        "# Function to convert cost to USD\n",
        "def convert_to_usd(currency, cost):\n",
        "    exchange_rate = exchange_rates.get(currency, 1.0)  # Default to 1.0 if currency not found\n",
        "    return cost * exchange_rate\n",
        "\n",
        "# Update 'cost' column with cost in USD\n",
        "df['cost'] = df.apply(lambda row: convert_to_usd(row['currency'], row['cost']), axis=1)\n",
        "\n",
        "# leaving currency column to determine locality\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "7S_5mUcmlIRo"
      },
      "outputs": [],
      "source": [
        "df['date'] = pd.to_datetime(df['date'])\n",
        "df['year'] = df['date'].dt.year\n",
        "df['month'] = df['date'].dt.month\n",
        "df['day'] = df['date'].dt.day"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HnxeO_r1g7Qn",
        "outputId": "a4ace8ab-00ad-47be-c983-bc3f152c6e4a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array(['EXPANDED_TEXT_AD', 'EXPANDED_DYNAMIC_SEARCH_AD'], dtype=object)"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# display rows with ID ID_5e43c29e6279884e2827d894\n",
        "\n",
        "df.loc[df['ID'] == 'ID_5e43c29e6279884e2827d894']['ad_type'].unique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "HjIyOtGslIRp",
        "outputId": "e5cb5fd1-0421-4c1d-9ca7-4b610a5058d8"
      },
      "outputs": [],
      "source": [
        "# one hot encode currency and ad_type\n",
        "\n",
        "df = pd.get_dummies(df, columns=['currency', 'ad_type'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "-pixGVsQg7Qo"
      },
      "outputs": [],
      "source": [
        "y = df['clicks']\n",
        "X = df.drop(columns=['ID', 'clicks'])\n",
        "\n",
        "X = X.drop(['date'], axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "TNVyqLkpg7Qp"
      },
      "outputs": [],
      "source": [
        "from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "# Standardize features\n",
        "scaler = StandardScaler()\n",
        "X_scaled = scaler.fit_transform(X)\n",
        "X = pd.DataFrame(X_scaled, columns=X.columns)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "55icqBX0g7Qq"
      },
      "outputs": [],
      "source": [
        "_prepd_df = pd.concat([X, y], axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 568
        },
        "id": "NXT-Euskg7Qr",
        "outputId": "8d3cfdcd-257b-468d-ef5e-5596656f277b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# plot correlation matrix\n",
        "import seaborn as sns\n",
        "\n",
        "corr = _prepd_df.corr()\n",
        "\n",
        "sns.heatmap(corr, annot=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tdVzJsOYg7Qs",
        "outputId": "ac3fc3bf-f021-48af-8ab3-63394486bc6c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "clicks                                1.000000\n",
              "impressions                           0.734686\n",
              "cost                                  0.278523\n",
              "headline2_len                         0.144910\n",
              "conversions                           0.128776\n",
              "impression_share                      0.126332\n",
              "ad_description_len                    0.077180\n",
              "headline1_len                         0.075684\n",
              "ad_type_RESPONSIVE_SEARCH_AD          0.066658\n",
              "conversions_calls                     0.038814\n",
              "year                                  0.030796\n",
              "currency_ZAR                          0.016201\n",
              "day                                  -0.002419\n",
              "month                                -0.014417\n",
              "currency_USD                         -0.016201\n",
              "ad_type_EXPANDED_TEXT_AD             -0.019154\n",
              "ad_type_EXPANDED_DYNAMIC_SEARCH_AD   -0.060715\n",
              "Name: clicks, dtype: float64"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# from corr matrix, show features correlation with clicks\n",
        "\n",
        "corr['clicks'].sort_values(ascending=False)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "Bt4Omufmg7Qt"
      },
      "outputs": [],
      "source": [
        "# using the features with correlation > 0.1 from corr['clicks']\n",
        "\n",
        "corr_features = corr['clicks'][corr['clicks'] > 0].index.drop('clicks')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "SYedaTPXg7Qt"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "x = X[corr_features]\n",
        "# y = df['clicks']\n",
        "\n",
        "# # add date features for time series\n",
        "x['year'] = X['year']\n",
        "x['month'] = X['month']\n",
        "x['day'] = X['day']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "N-KWCQkBg7Qu",
        "outputId": "817fc89d-a8b3-404f-a7b4-5f158c1bbd9b"
      },
      "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>impressions</th>\n",
              "      <th>cost</th>\n",
              "      <th>conversions</th>\n",
              "      <th>impression_share</th>\n",
              "      <th>conversions_calls</th>\n",
              "      <th>headline1_len</th>\n",
              "      <th>headline2_len</th>\n",
              "      <th>ad_description_len</th>\n",
              "      <th>year</th>\n",
              "      <th>currency_ZAR</th>\n",
              "      <th>ad_type_RESPONSIVE_SEARCH_AD</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.450480</td>\n",
              "      <td>0.136493</td>\n",
              "      <td>-0.076726</td>\n",
              "      <td>-0.032266</td>\n",
              "      <td>-0.239826</td>\n",
              "      <td>-0.47456</td>\n",
              "      <td>1.269298</td>\n",
              "      <td>0.065160</td>\n",
              "      <td>-2.43374</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.709693</td>\n",
              "      <td>-1.602911</td>\n",
              "      <td>-1.667347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.105411</td>\n",
              "      <td>-0.072893</td>\n",
              "      <td>-0.076726</td>\n",
              "      <td>-0.032266</td>\n",
              "      <td>-0.239826</td>\n",
              "      <td>-0.47456</td>\n",
              "      <td>-0.526729</td>\n",
              "      <td>0.508674</td>\n",
              "      <td>-2.43374</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.709693</td>\n",
              "      <td>-1.602911</td>\n",
              "      <td>-1.667347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.089911</td>\n",
              "      <td>-0.082724</td>\n",
              "      <td>-0.076726</td>\n",
              "      <td>-0.032266</td>\n",
              "      <td>-0.239826</td>\n",
              "      <td>-0.47456</td>\n",
              "      <td>-0.526729</td>\n",
              "      <td>-0.156597</td>\n",
              "      <td>-2.43374</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.709693</td>\n",
              "      <td>-1.602911</td>\n",
              "      <td>-1.667347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.033793</td>\n",
              "      <td>-0.192465</td>\n",
              "      <td>-0.076726</td>\n",
              "      <td>-0.032266</td>\n",
              "      <td>-0.239826</td>\n",
              "      <td>-0.47456</td>\n",
              "      <td>0.071946</td>\n",
              "      <td>0.508674</td>\n",
              "      <td>-2.43374</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.709693</td>\n",
              "      <td>-1.602911</td>\n",
              "      <td>-1.667347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.343829</td>\n",
              "      <td>-0.285467</td>\n",
              "      <td>-0.076726</td>\n",
              "      <td>-0.032266</td>\n",
              "      <td>-0.239826</td>\n",
              "      <td>-0.47456</td>\n",
              "      <td>-0.526729</td>\n",
              "      <td>0.508674</td>\n",
              "      <td>-2.43374</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.709693</td>\n",
              "      <td>-1.602911</td>\n",
              "      <td>-1.667347</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   impressions      cost  conversions  impression_share  conversions_calls  \\\n",
              "0     0.450480  0.136493    -0.076726         -0.032266          -0.239826   \n",
              "1     0.105411 -0.072893    -0.076726         -0.032266          -0.239826   \n",
              "2    -0.089911 -0.082724    -0.076726         -0.032266          -0.239826   \n",
              "3     0.033793 -0.192465    -0.076726         -0.032266          -0.239826   \n",
              "4    -0.343829 -0.285467    -0.076726         -0.032266          -0.239826   \n",
              "\n",
              "   headline1_len  headline2_len  ad_description_len     year  currency_ZAR  \\\n",
              "0       -0.47456       1.269298            0.065160 -2.43374      0.233002   \n",
              "1       -0.47456      -0.526729            0.508674 -2.43374      0.233002   \n",
              "2       -0.47456      -0.526729           -0.156597 -2.43374      0.233002   \n",
              "3       -0.47456       0.071946            0.508674 -2.43374      0.233002   \n",
              "4       -0.47456      -0.526729            0.508674 -2.43374      0.233002   \n",
              "\n",
              "   ad_type_RESPONSIVE_SEARCH_AD     month       day  \n",
              "0                     -0.709693 -1.602911 -1.667347  \n",
              "1                     -0.709693 -1.602911 -1.667347  \n",
              "2                     -0.709693 -1.602911 -1.667347  \n",
              "3                     -0.709693 -1.602911 -1.667347  \n",
              "4                     -0.709693 -1.602911 -1.667347  "
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "x.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gYQ8k-AVg7Qu",
        "outputId": "bc30e499-f224-4480-ac00-a89ee80db064"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# length check\n",
        "len(x) == len(y)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "GmrdqrHbg7Qv"
      },
      "outputs": [],
      "source": [
        "# train test split\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=42)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jh1v6Rnnq6HS"
      },
      "source": [
        "# models"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RBegWz4tg7Qv",
        "outputId": "88981542-c005-432d-bb1b-bced9840054c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Trainig  RandomForest\n",
            "RandomForest |--| Mean Squared Error: 22.87558464580527, |--| Root Mean Squared Error: 4.782842736888311\n"
          ]
        }
      ],
      "source": [
        "import xgboost as xgb\n",
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from sklearn.linear_model import LinearRegression, ElasticNet, BayesianRidge\n",
        "# from sklearn.svm import SVR\n",
        "from sklearn.neighbors import KNeighborsRegressor\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "from sklearn.gaussian_process import GaussianProcessRegressor\n",
        "from sklearn.neural_network import MLPRegressor\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from math import sqrt\n",
        "\n",
        "# Initialize and train models\n",
        "models = {\n",
        "    # \"XGBoost\": xgb.XGBRegressor(objective='reg:squarederror', n_estimators=1000, learning_rate=0.1, max_depth=3),\n",
        "    \"RandomForest\": RandomForestRegressor(n_estimators=100, random_state=42),\n",
        "    # \"LinearRegression\": LinearRegression(),\n",
        "    # \"ElasticNet\": ElasticNet(),\n",
        "    # \"BayesianRidge\": BayesianRidge(),\n",
        "    # \"KNeighborsRegressor\": KNeighborsRegressor(),\n",
        "    # \"DecisionTreeRegressor\": DecisionTreeRegressor(),\n",
        "    # \"MLPRegressor\": MLPRegressor()\n",
        "}\n",
        "\n",
        "# Train and evaluate models\n",
        "results = {}\n",
        "for name, model in models.items():\n",
        "    print(\"Trainig \", name)\n",
        "    try:\n",
        "        model.fit(x_train, y_train)\n",
        "        predictions = model.predict(x_test)\n",
        "        mse = mean_squared_error(y_test, predictions)\n",
        "        results[name] = mse\n",
        "    except Exception as e:\n",
        "        print(f\"Error occurred while training {name}: {e}\")\n",
        "        results[name] = None  # Set MSE to None if an error occurs\n",
        "\n",
        "\n",
        "\n",
        "# Print results\n",
        "for name, mse in results.items():\n",
        "    if mse is not None:\n",
        "        rmse = sqrt(mse)\n",
        "        print(f\"{name} |--| Mean Squared Error: {mse}, |--| Root Mean Squared Error: {rmse}\")\n",
        "    else:\n",
        "        print(f\"{name} failed to train.\")\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2ZLK_MXelISA"
      },
      "source": [
        "# neural Net"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YBSQCNsrmEpR"
      },
      "outputs": [],
      "source": [
        "# %%capture\n",
        "# !pip install tensorflow"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "bfxsxzt-0gdW"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Dense, LSTM\n",
        "from tensorflow.keras.optimizers import Adam\n",
        "from tensorflow.keras.layers import Normalization\n",
        "from tensorflow.keras.layers import Dropout"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q1_5_A-XlISB",
        "outputId": "f1387ca9-7730-4790-88e2-3a5e0e840c9c"
      },
      "outputs": [],
      "source": [
        "model = Sequential([\n",
        "    Dense(64, activation='relu',input_shape=(x_train.shape[1], )),\n",
        "    Dense(32, activation='relu'),\n",
        "    Dense(1)\n",
        "])\n",
        "\n",
        "# Compile model\n",
        "model.compile(optimizer=Adam(learning_rate=0.001), loss='mean_squared_error')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from keras.callbacks import EarlyStopping\n",
        "\n",
        "early_stop = EarlyStopping(monitor='val_loss', patience=10)\n",
        "\n",
        "history = model.fit(x_train, y_train, batch_size=32, epochs=50, validation_split=0.2, verbose=1, callbacks=early_stop)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ybyslLbInwoq"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Plot training & validation loss values\n",
        "plt.plot(history.history['loss'])\n",
        "plt.plot(history.history['val_loss'])\n",
        "plt.title('Model loss')\n",
        "plt.ylabel('Loss')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I0-6yb3Yr3r1"
      },
      "source": [
        "# Submision file Generation / inference\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "fdGSrLtwycjt"
      },
      "outputs": [],
      "source": [
        "model_choice = \"RandomForest\"\n",
        "model = models[model_choice]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3wEQlTuSg7Qw",
        "outputId": "707ff00b-7fd8-40c0-fda1-d7e5d4ee48fc"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "RMSE: 4.782842736888311\n",
            "MSE: 22.87558464580527\n"
          ]
        }
      ],
      "source": [
        "# model evaluation\n",
        "from sklearn.metrics import mean_squared_error\n",
        "\n",
        "# Evaluate model\n",
        "y_pred = model.predict(x_test)\n",
        "y_pred = y_pred.flatten()\n",
        "\n",
        "mse = mean_squared_error(y_test, y_pred)\n",
        "rmse = np.sqrt(mse)\n",
        "\n",
        "print(f'RMSE: {rmse}')\n",
        "print(f'MSE: {mse}')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "id": "f028USZkg7Qx"
      },
      "outputs": [],
      "source": [
        "def extract_id_and_date(string):\n",
        "    parts = string.split('_')\n",
        "    id_str = parts[1]\n",
        "    date_str = '_'.join(parts[2:])\n",
        "    return \"ID_\" + id_str, pd.to_datetime(date_str, format='%Y_%m_%d')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "metadata": {
        "id": "zjHGkGITg7Qx"
      },
      "outputs": [],
      "source": [
        "# submission file\n",
        "test_df = pd.read_csv('datasets/SampleSubmission.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "metadata": {
        "id": "0UExOeUqg7Qx"
      },
      "outputs": [],
      "source": [
        "test_df['id'], test_df['date'] = zip(*test_df['ID'].map(extract_id_and_date))\n",
        "test_df['end_date'] = test_df['date'] + pd.Timedelta(days=20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "3NiBqrhYg7Qy",
        "outputId": "ff6d219b-5a60-48bb-d98d-538ab2be8ef2"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>ID</th>\n",
              "      <th>clicks</th>\n",
              "      <th>id</th>\n",
              "      <th>date</th>\n",
              "      <th>end_date</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046_2024_01_22</td>\n",
              "      <td>0</td>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046</td>\n",
              "      <td>2024-01-22</td>\n",
              "      <td>2024-02-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046_2024_01_29</td>\n",
              "      <td>0</td>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046</td>\n",
              "      <td>2024-01-29</td>\n",
              "      <td>2024-02-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ID_5e43c29e6279884e2827d894_2024_02_21</td>\n",
              "      <td>0</td>\n",
              "      <td>ID_5e43c29e6279884e2827d894</td>\n",
              "      <td>2024-02-21</td>\n",
              "      <td>2024-03-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ID_5e43c29e6279884e2827d894_2024_02_28</td>\n",
              "      <td>0</td>\n",
              "      <td>ID_5e43c29e6279884e2827d894</td>\n",
              "      <td>2024-02-28</td>\n",
              "      <td>2024-03-19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ID_5e4e7b480e374330ee151305_2023_12_04</td>\n",
              "      <td>0</td>\n",
              "      <td>ID_5e4e7b480e374330ee151305</td>\n",
              "      <td>2023-12-04</td>\n",
              "      <td>2023-12-24</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                       ID  clicks  \\\n",
              "0  ID_5da86e71bf5dee4cf5047046_2024_01_22       0   \n",
              "1  ID_5da86e71bf5dee4cf5047046_2024_01_29       0   \n",
              "2  ID_5e43c29e6279884e2827d894_2024_02_21       0   \n",
              "3  ID_5e43c29e6279884e2827d894_2024_02_28       0   \n",
              "4  ID_5e4e7b480e374330ee151305_2023_12_04       0   \n",
              "\n",
              "                            id       date   end_date  \n",
              "0  ID_5da86e71bf5dee4cf5047046 2024-01-22 2024-02-11  \n",
              "1  ID_5da86e71bf5dee4cf5047046 2024-01-29 2024-02-18  \n",
              "2  ID_5e43c29e6279884e2827d894 2024-02-21 2024-03-12  \n",
              "3  ID_5e43c29e6279884e2827d894 2024-02-28 2024-03-19  \n",
              "4  ID_5e4e7b480e374330ee151305 2023-12-04 2023-12-24  "
            ]
          },
          "execution_count": 57,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "test_df.head(2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "lqEDVI_Ig7Qy",
        "outputId": "ca2451ba-a46b-4066-f39c-bf688ce1e68b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'ID_5da86e71bf5dee4cf5047046'"
            ]
          },
          "execution_count": 58,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "test_row = test_df.iloc[0]\n",
        "test_row['id']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 59,
      "metadata": {
        "id": "ZZDdVREmg7Qy"
      },
      "outputs": [],
      "source": [
        "\n",
        "XX = X.copy()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "metadata": {
        "id": "PtgtARN6g7Qz"
      },
      "outputs": [],
      "source": [
        "XX['date'] = pd.to_datetime(df['date'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "metadata": {
        "id": "DPXlv7r_g7Qz"
      },
      "outputs": [],
      "source": [
        "XX['ID'] = df['ID']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 215
        },
        "id": "Flxjjn5eg7Qz",
        "outputId": "f14c5951-299e-4bc6-9282-a10da0603095"
      },
      "outputs": [
        {
          "data": {
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>impressions</th>\n",
              "      <th>cost</th>\n",
              "      <th>conversions</th>\n",
              "      <th>impression_share</th>\n",
              "      <th>conversions_calls</th>\n",
              "      <th>headline1_len</th>\n",
              "      <th>headline2_len</th>\n",
              "      <th>ad_description_len</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "      <th>currency_USD</th>\n",
              "      <th>currency_ZAR</th>\n",
              "      <th>ad_type_EXPANDED_DYNAMIC_SEARCH_AD</th>\n",
              "      <th>ad_type_EXPANDED_TEXT_AD</th>\n",
              "      <th>ad_type_RESPONSIVE_SEARCH_AD</th>\n",
              "      <th>date</th>\n",
              "      <th>ID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <td>-0.47456</td>\n",
              "      <td>1.269298</td>\n",
              "      <td>0.065160</td>\n",
              "      <td>-2.43374</td>\n",
              "      <td>-1.602911</td>\n",
              "      <td>-1.667347</td>\n",
              "      <td>-0.233002</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.425844</td>\n",
              "      <td>0.977188</td>\n",
              "      <td>-0.709693</td>\n",
              "      <td>2020-01-01</td>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046</td>\n",
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              "      <td>-0.072893</td>\n",
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              "      <td>0.508674</td>\n",
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              "      <td>2020-01-01</td>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>-0.076726</td>\n",
              "      <td>-0.032266</td>\n",
              "      <td>-0.239826</td>\n",
              "      <td>-0.47456</td>\n",
              "      <td>-0.526729</td>\n",
              "      <td>-0.156597</td>\n",
              "      <td>-2.43374</td>\n",
              "      <td>-1.602911</td>\n",
              "      <td>-1.667347</td>\n",
              "      <td>-0.233002</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.425844</td>\n",
              "      <td>0.977188</td>\n",
              "      <td>-0.709693</td>\n",
              "      <td>2020-01-01</td>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   impressions      cost  conversions  impression_share  conversions_calls  \\\n",
              "0     0.450480  0.136493    -0.076726         -0.032266          -0.239826   \n",
              "1     0.105411 -0.072893    -0.076726         -0.032266          -0.239826   \n",
              "2    -0.089911 -0.082724    -0.076726         -0.032266          -0.239826   \n",
              "\n",
              "   headline1_len  headline2_len  ad_description_len     year     month  \\\n",
              "0       -0.47456       1.269298            0.065160 -2.43374 -1.602911   \n",
              "1       -0.47456      -0.526729            0.508674 -2.43374 -1.602911   \n",
              "2       -0.47456      -0.526729           -0.156597 -2.43374 -1.602911   \n",
              "\n",
              "        day  currency_USD  currency_ZAR  ad_type_EXPANDED_DYNAMIC_SEARCH_AD  \\\n",
              "0 -1.667347     -0.233002      0.233002                           -0.425844   \n",
              "1 -1.667347     -0.233002      0.233002                           -0.425844   \n",
              "2 -1.667347     -0.233002      0.233002                           -0.425844   \n",
              "\n",
              "   ad_type_EXPANDED_TEXT_AD  ad_type_RESPONSIVE_SEARCH_AD       date  \\\n",
              "0                  0.977188                     -0.709693 2020-01-01   \n",
              "1                  0.977188                     -0.709693 2020-01-01   \n",
              "2                  0.977188                     -0.709693 2020-01-01   \n",
              "\n",
              "                            ID  \n",
              "0  ID_5da86e71bf5dee4cf5047046  \n",
              "1  ID_5da86e71bf5dee4cf5047046  \n",
              "2  ID_5da86e71bf5dee4cf5047046  "
            ]
          },
          "execution_count": 62,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "XX.head(3)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "755kyTeug7Q0",
        "outputId": "6d17237c-22df-4d76-a7f8-bbce1203964f"
      },
      "outputs": [],
      "source": [
        "def filter_df_by_id_or_date_range(df, id, start_date, end_date, sample=False):\n",
        "    \"\"\"\n",
        "    Filter DataFrame by ID or date range.\n",
        "\n",
        "    Args:\n",
        "    df (DataFrame): Input DataFrame to filter.\n",
        "    id (str): ID to filter.\n",
        "    start_date (str or Timestamp): Start date of the range.\n",
        "    end_date (str or Timestamp): End date of the range.\n",
        "\n",
        "    Returns:\n",
        "    DataFrame: Filtered DataFrame containing rows within the specified ID or date range.\n",
        "    \"\"\"\n",
        "    filtered = df[(( df['ID'].str.contains('id') ) & (df['date'] >= start_date)) | ((df['ID'] == id) & (df['date'] <= end_date))]\n",
        "    if sample: return filtered\n",
        "    return filtered[x.columns].mean().to_frame().T"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>impressions</th>\n",
              "      <th>cost</th>\n",
              "      <th>conversions</th>\n",
              "      <th>impression_share</th>\n",
              "      <th>conversions_calls</th>\n",
              "      <th>headline1_len</th>\n",
              "      <th>headline2_len</th>\n",
              "      <th>ad_description_len</th>\n",
              "      <th>year</th>\n",
              "      <th>currency_ZAR</th>\n",
              "      <th>ad_type_RESPONSIVE_SEARCH_AD</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.113102</td>\n",
              "      <td>-0.146347</td>\n",
              "      <td>-0.07629</td>\n",
              "      <td>0.102439</td>\n",
              "      <td>-0.14201</td>\n",
              "      <td>-0.486618</td>\n",
              "      <td>-0.426713</td>\n",
              "      <td>0.071322</td>\n",
              "      <td>-0.818766</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>-0.134063</td>\n",
              "      <td>-0.058706</td>\n",
              "      <td>-0.013788</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   impressions      cost  conversions  impression_share  conversions_calls  \\\n",
              "0     0.113102 -0.146347     -0.07629          0.102439           -0.14201   \n",
              "\n",
              "   headline1_len  headline2_len  ad_description_len      year  currency_ZAR  \\\n",
              "0      -0.486618      -0.426713            0.071322 -0.818766      0.233002   \n",
              "\n",
              "   ad_type_RESPONSIVE_SEARCH_AD     month       day  \n",
              "0                     -0.134063 -0.058706 -0.013788  "
            ]
          },
          "execution_count": 74,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# test row\n",
        "test_row = test_df.iloc[0]\n",
        "\n",
        "filetered_df_t = filter_df_by_id_or_date_range(XX, test_row['id'], test_row['date'], test_row['end_date'])\n",
        "\n",
        "filetered_df_t"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Iterate over each row in test_df\n",
        "for index, test_row in test_df.iterrows():\n",
        "    # Filter rows in XX based on the ID or date range from the current row\n",
        "    filtered_df = filter_df_by_id_or_date_range(XX, test_row['id'], test_row['date'], test_row['end_date'])\n",
        "    # Predict clicks for the filtered data\n",
        "    clicks_predict = model.predict(filtered_df)\n",
        "    # Calculate sum of clicks and update the 'clicks' column in test_df\n",
        "    test_df.at[index, 'clicks'] = int(clicks_predict)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
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              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "\n",
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              "    }\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>impressions</th>\n",
              "      <th>cost</th>\n",
              "      <th>conversions</th>\n",
              "      <th>impression_share</th>\n",
              "      <th>conversions_calls</th>\n",
              "      <th>headline1_len</th>\n",
              "      <th>headline2_len</th>\n",
              "      <th>ad_description_len</th>\n",
              "      <th>year</th>\n",
              "      <th>currency_ZAR</th>\n",
              "      <th>ad_type_RESPONSIVE_SEARCH_AD</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.444775</td>\n",
              "      <td>0.024965</td>\n",
              "      <td>-0.076726</td>\n",
              "      <td>-0.548656</td>\n",
              "      <td>-0.239826</td>\n",
              "      <td>-1.220168</td>\n",
              "      <td>0.305715</td>\n",
              "      <td>0.221446</td>\n",
              "      <td>1.894952</td>\n",
              "      <td>0.233002</td>\n",
              "      <td>1.045845</td>\n",
              "      <td>-1.448017</td>\n",
              "      <td>0.082178</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   impressions      cost  conversions  impression_share  conversions_calls  \\\n",
              "0     0.444775  0.024965    -0.076726         -0.548656          -0.239826   \n",
              "\n",
              "   headline1_len  headline2_len  ad_description_len      year  currency_ZAR  \\\n",
              "0      -1.220168       0.305715            0.221446  1.894952      0.233002   \n",
              "\n",
              "   ad_type_RESPONSIVE_SEARCH_AD     month       day  \n",
              "0                      1.045845 -1.448017  0.082178  "
            ]
          },
          "execution_count": 83,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "filtered_df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 84,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Xt2R4Eqkg7Q0",
        "outputId": "24285b8e-1975-4b0b-d493-d563a46a71be"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "execution_count": 84,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# count clicks with 0s\n",
        "test_df[test_df['clicks'] == 0].shape[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "KCBjFYDgg7Q0",
        "outputId": "81c40600-335b-457d-b709-c193e0a53cf6"
      },
      "outputs": [
        {
          "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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              "        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>ID</th>\n",
              "      <th>clicks</th>\n",
              "      <th>id</th>\n",
              "      <th>date</th>\n",
              "      <th>end_date</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046_2024_01_22</td>\n",
              "      <td>9</td>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046</td>\n",
              "      <td>2024-01-22</td>\n",
              "      <td>2024-02-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046_2024_01_29</td>\n",
              "      <td>9</td>\n",
              "      <td>ID_5da86e71bf5dee4cf5047046</td>\n",
              "      <td>2024-01-29</td>\n",
              "      <td>2024-02-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ID_5e43c29e6279884e2827d894_2024_02_21</td>\n",
              "      <td>3</td>\n",
              "      <td>ID_5e43c29e6279884e2827d894</td>\n",
              "      <td>2024-02-21</td>\n",
              "      <td>2024-03-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ID_5e43c29e6279884e2827d894_2024_02_28</td>\n",
              "      <td>3</td>\n",
              "      <td>ID_5e43c29e6279884e2827d894</td>\n",
              "      <td>2024-02-28</td>\n",
              "      <td>2024-03-19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ID_5e4e7b480e374330ee151305_2023_12_04</td>\n",
              "      <td>3</td>\n",
              "      <td>ID_5e4e7b480e374330ee151305</td>\n",
              "      <td>2023-12-04</td>\n",
              "      <td>2023-12-24</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                       ID  clicks  \\\n",
              "0  ID_5da86e71bf5dee4cf5047046_2024_01_22       9   \n",
              "1  ID_5da86e71bf5dee4cf5047046_2024_01_29       9   \n",
              "2  ID_5e43c29e6279884e2827d894_2024_02_21       3   \n",
              "3  ID_5e43c29e6279884e2827d894_2024_02_28       3   \n",
              "4  ID_5e4e7b480e374330ee151305_2023_12_04       3   \n",
              "\n",
              "                            id       date   end_date  \n",
              "0  ID_5da86e71bf5dee4cf5047046 2024-01-22 2024-02-11  \n",
              "1  ID_5da86e71bf5dee4cf5047046 2024-01-29 2024-02-18  \n",
              "2  ID_5e43c29e6279884e2827d894 2024-02-21 2024-03-12  \n",
              "3  ID_5e43c29e6279884e2827d894 2024-02-28 2024-03-19  \n",
              "4  ID_5e4e7b480e374330ee151305 2023-12-04 2023-12-24  "
            ]
          },
          "execution_count": 85,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "test_df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 86,
      "metadata": {
        "id": "6Wayjpvzg7Q0"
      },
      "outputs": [],
      "source": [
        "test_df.to_csv(\"s0ep_nn_attempt.csv\", index=False)"
      ]
    }
  ],
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    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
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