2148 lines
568 KiB
Plaintext
2148 lines
568 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "3415114e-9577-4487-89eb-4931620ad9f0",
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"metadata": {},
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"source": [
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"# Predict Sales"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "f271eb45-1470-4764-8c2e-31374efa1fe5",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"import os\n",
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"import s3fs\n",
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"import re\n",
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"from sklearn.linear_model import LogisticRegression\n",
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"from sklearn.ensemble import RandomForestClassifier\n",
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"from sklearn.metrics import accuracy_score, confusion_matrix, classification_report, recall_score\n",
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"from sklearn.utils import class_weight\n",
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"from sklearn.neighbors import KNeighborsClassifier\n",
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"from sklearn.pipeline import Pipeline\n",
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"from sklearn.compose import ColumnTransformer\n",
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"from sklearn.preprocessing import OneHotEncoder\n",
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"from sklearn.impute import SimpleImputer\n",
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"from sklearn.model_selection import GridSearchCV\n",
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"from sklearn.preprocessing import StandardScaler, MaxAbsScaler, MinMaxScaler\n",
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"from sklearn.metrics import make_scorer, f1_score, balanced_accuracy_score\n",
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"import seaborn as sns\n",
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"import matplotlib.pyplot as plt\n",
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"from sklearn.metrics import roc_curve, auc, precision_recall_curve, average_precision_score\n",
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"from sklearn.exceptions import ConvergenceWarning, DataConversionWarning\n",
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"\n",
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"import pickle\n",
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"import warnings\n",
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"#import scikitplot as skplt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "3fecb606-22e5-4dee-8efa-f8dff0832299",
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"metadata": {},
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"outputs": [],
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"source": [
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"warnings.filterwarnings('ignore')\n",
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"warnings.filterwarnings(\"ignore\", category=ConvergenceWarning)\n",
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"warnings.filterwarnings(\"ignore\", category=DataConversionWarning)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ae591854-3003-4c75-a0c7-5abf04246e81",
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"metadata": {},
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"source": [
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"### Load Data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "59dd4694-a812-4923-b995-a2ee86c74f85",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Create filesystem object\n",
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"S3_ENDPOINT_URL = \"https://\" + os.environ[\"AWS_S3_ENDPOINT\"]\n",
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"fs = s3fs.S3FileSystem(client_kwargs={'endpoint_url': S3_ENDPOINT_URL})"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "017f7e9a-3ba0-40fa-bdc8-51b98cc1fdb3",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_train_test():\n",
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" BUCKET = \"projet-bdc2324-team1/Generalization/sport\"\n",
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" File_path_train = BUCKET + \"/Train_set.csv\"\n",
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" File_path_test = BUCKET + \"/Test_set.csv\"\n",
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" \n",
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" with fs.open( File_path_train, mode=\"rb\") as file_in:\n",
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" dataset_train = pd.read_csv(file_in, sep=\",\")\n",
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" # dataset_train['y_has_purchased'] = dataset_train['y_has_purchased'].fillna(0)\n",
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"\n",
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" with fs.open(File_path_test, mode=\"rb\") as file_in:\n",
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" dataset_test = pd.read_csv(file_in, sep=\",\")\n",
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" # dataset_test['y_has_purchased'] = dataset_test['y_has_purchased'].fillna(0)\n",
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" \n",
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" return dataset_train, dataset_test"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "c479b230-b4bd-4cfb-b76b-d9faf6d95772",
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"metadata": {},
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"outputs": [],
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"source": [
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"dataset_train, dataset_test = load_train_test()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "c24c446d-4e1c-4ac1-a048-f0b8d8559f36",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"customer_id 0\n",
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"nb_tickets 0\n",
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"nb_purchases 0\n",
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"total_amount 0\n",
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"nb_suppliers 0\n",
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"vente_internet_max 0\n",
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"purchase_date_min 0\n",
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"purchase_date_max 0\n",
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"time_between_purchase 0\n",
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"nb_tickets_internet 0\n",
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"street_id 0\n",
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"structure_id 222825\n",
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"mcp_contact_id 70874\n",
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"fidelity 0\n",
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"tenant_id 0\n",
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"is_partner 0\n",
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"deleted_at 224213\n",
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"gender 0\n",
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"is_email_true 0\n",
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"opt_in 0\n",
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"last_buying_date 66139\n",
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"max_price 66139\n",
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"ticket_sum 0\n",
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"average_price 66023\n",
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"average_purchase_delay 66139\n",
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"average_price_basket 66139\n",
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"average_ticket_basket 66139\n",
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"total_price 116\n",
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"purchase_count 0\n",
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"first_buying_date 66139\n",
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"country 23159\n",
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"gender_label 0\n",
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"gender_female 0\n",
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"gender_male 0\n",
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"gender_other 0\n",
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"country_fr 23159\n",
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"nb_campaigns 0\n",
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"nb_campaigns_opened 0\n",
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"time_to_open 123159\n",
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"y_has_purchased 0\n",
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"dtype: int64"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dataset_train.isna().sum()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "825d14a3-6967-4733-bfd4-64bf61c2bd43",
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"metadata": {},
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"outputs": [],
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"source": [
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"def features_target_split(dataset_train, dataset_test):\n",
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" features_l = ['nb_tickets', 'nb_purchases', 'total_amount', 'nb_suppliers', 'vente_internet_max', 'purchase_date_min', 'purchase_date_max', \n",
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" 'time_between_purchase', 'nb_tickets_internet', 'fidelity', 'is_email_true', 'opt_in', #'is_partner',\n",
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" 'gender_female', 'gender_male', 'gender_other', 'nb_campaigns', 'nb_campaigns_opened']\n",
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" X_train = dataset_train[features_l]\n",
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" y_train = dataset_train[['y_has_purchased']]\n",
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"\n",
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" X_test = dataset_test[features_l]\n",
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" y_test = dataset_test[['y_has_purchased']]\n",
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" return X_train, X_test, y_train, y_test"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "69eaec12-b30f-4d30-a461-ea520d5cbf77",
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"metadata": {},
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"outputs": [],
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"source": [
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"X_train, X_test, y_train, y_test = features_target_split(dataset_train, dataset_test)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "d039f31d-0093-46c6-9743-ddec1381f758",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Shape train : (224213, 17)\n",
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"Shape test : (96096, 17)\n"
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]
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}
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],
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"source": [
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"print(\"Shape train : \", X_train.shape)\n",
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"print(\"Shape test : \", X_test.shape)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a1d6de94-4e11-481a-a0ce-412bf29f692c",
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"metadata": {},
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"source": [
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"### Prepare preprocessing and Hyperparameters"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "b808da43-c444-4e94-995a-7ec6ccd01e2d",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{0.0: 0.5837086520288036, 1.0: 3.486549107420539}"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Compute Weights\n",
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"weights = class_weight.compute_class_weight(class_weight = 'balanced', classes = np.unique(y_train['y_has_purchased']),\n",
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" y = y_train['y_has_purchased'])\n",
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"\n",
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"weight_dict = {np.unique(y_train['y_has_purchased'])[i]: weights[i] for i in range(len(np.unique(y_train['y_has_purchased'])))}\n",
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"weight_dict"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "b32a79ea-907f-4dfc-9832-6c74bef3200c",
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"metadata": {},
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"outputs": [],
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"source": [
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"numeric_features = ['nb_tickets', 'nb_purchases', 'total_amount', 'nb_suppliers', 'vente_internet_max', 'purchase_date_min', 'purchase_date_max', \n",
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" 'time_between_purchase', 'nb_tickets_internet', 'fidelity', 'is_email_true', 'opt_in', #'is_partner',\n",
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" 'gender_female', 'gender_male', 'gender_other', 'nb_campaigns', 'nb_campaigns_opened']\n",
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"\n",
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"numeric_transformer = Pipeline(steps=[\n",
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" #(\"imputer\", SimpleImputer(strategy=\"mean\")), \n",
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" (\"scaler\", StandardScaler()) \n",
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"])\n",
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"\n",
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"categorical_features = ['opt_in'] \n",
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"\n",
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"# Transformer for the categorical features\n",
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"categorical_transformer = Pipeline(steps=[\n",
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" #(\"imputer\", SimpleImputer(strategy=\"most_frequent\")), # Impute missing values with the most frequent\n",
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" (\"onehot\", OneHotEncoder(handle_unknown='ignore', sparse_output=False))\n",
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"])\n",
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"\n",
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"preproc = ColumnTransformer(\n",
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" transformers=[\n",
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" (\"num\", numeric_transformer, numeric_features),\n",
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" (\"cat\", categorical_transformer, categorical_features)\n",
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" ]\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "9809a688-bfbc-4685-a77f-17a8b2b79ab3",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Set loss\n",
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"balanced_scorer = make_scorer(balanced_accuracy_score)\n",
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"recall_scorer = make_scorer(recall_score)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "4f9b2bbf-5f8a-4ac1-8e6c-51bd0dd8ac85",
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"metadata": {},
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"outputs": [],
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"source": [
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"def draw_confusion_matrix(y_test, y_pred):\n",
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" conf_matrix = confusion_matrix(y_test, y_pred)\n",
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" sns.heatmap(conf_matrix, annot=True, fmt='d', cmap='Blues', xticklabels=['Class 0', 'Class 1'], yticklabels=['Class 0', 'Class 1'])\n",
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" plt.xlabel('Predicted')\n",
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" plt.ylabel('Actual')\n",
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" plt.title('Confusion Matrix')\n",
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" plt.show()\n",
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"\n",
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"\n",
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"def draw_roc_curve(X_test, y_test):\n",
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" y_pred_prob = pipeline.predict_proba(X_test)[:, 1]\n",
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"\n",
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" # Calcul des taux de faux positifs (FPR) et de vrais positifs (TPR)\n",
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" fpr, tpr, thresholds = roc_curve(y_test, y_pred_prob, pos_label=1)\n",
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" \n",
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" # Calcul de l'aire sous la courbe ROC (AUC)\n",
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" roc_auc = auc(fpr, tpr)\n",
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" \n",
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" plt.figure(figsize = (14, 8))\n",
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" plt.plot(fpr, tpr, label=\"ROC curve(area = %0.3f)\" % roc_auc)\n",
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" plt.plot([0, 1], [0, 1], color=\"red\",label=\"Random Baseline\", linestyle=\"--\")\n",
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" plt.grid(color='gray', linestyle='--', linewidth=0.5)\n",
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" plt.xlabel('Taux de faux positifs (FPR)')\n",
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" plt.ylabel('Taux de vrais positifs (TPR)')\n",
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" plt.title('Courbe ROC : modèle logistique')\n",
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" plt.legend(loc=\"lower right\")\n",
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" plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "cf400c70-0192-42cc-9919-f61bae8382b0",
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"metadata": {},
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"outputs": [],
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"source": [
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"def draw_features_importance(pipeline, model):\n",
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" coefficients = pipeline.named_steps['logreg'].coef_[0]\n",
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" feature_names = pipeline.named_steps['logreg'].feature_names_in_\n",
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" \n",
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" # Tracer l'importance des caractéristiques\n",
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" plt.figure(figsize=(10, 6))\n",
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" plt.barh(feature_names, coefficients, color='skyblue')\n",
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" plt.xlabel('Importance des caractéristiques')\n",
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" plt.ylabel('Caractéristiques')\n",
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" plt.title('Importance des caractéristiques dans le modèle de régression logistique')\n",
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" plt.grid(True)\n",
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" plt.show()\n",
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"\n",
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"def draw_prob_distribution(X_test):\n",
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" y_pred_prob = pipeline.predict_proba(X_test)[:, 1]\n",
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" plt.figure(figsize=(8, 6))\n",
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" plt.hist(y_pred_prob, bins=10, range=(0, 1), color='blue', alpha=0.7)\n",
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" \n",
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" plt.xlim(0, 1)\n",
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" plt.ylim(0, None)\n",
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" \n",
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" plt.title('Histogramme des probabilités pour la classe 1')\n",
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" plt.xlabel('Probabilité')\n",
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" plt.ylabel('Fréquence')\n",
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" plt.grid(True)\n",
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" plt.show()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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|
"id": "206d9a95-7c37-4506-949b-e77d225e42c5",
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"metadata": {},
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|
"outputs": [],
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"source": [
|
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"# Hyperparameter\n",
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"param_grid = {'logreg__C': np.logspace(-10, 6, 17, base=2),\n",
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" 'logreg__penalty': ['l1', 'l2'],\n",
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" 'logreg__class_weight': ['balanced', weight_dict]} "
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]
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},
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{
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"cell_type": "code",
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|
"execution_count": 16,
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|
"id": "7ff2f7bd-efc1-4f7c-a3c9-caa916aa2f2b",
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"metadata": {},
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|
"outputs": [
|
|
{
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|
"data": {
|
|
"text/html": [
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"<style>#sk-container-id-1 {\n",
|
|
" /* Definition of color scheme common for light and dark mode */\n",
|
|
" --sklearn-color-text: black;\n",
|
|
" --sklearn-color-line: gray;\n",
|
|
" /* Definition of color scheme for unfitted estimators */\n",
|
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" --sklearn-color-unfitted-level-0: #fff5e6;\n",
|
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" --sklearn-color-unfitted-level-1: #f6e4d2;\n",
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" --sklearn-color-unfitted-level-2: #ffe0b3;\n",
|
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" --sklearn-color-unfitted-level-3: chocolate;\n",
|
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" /* Definition of color scheme for fitted estimators */\n",
|
|
" --sklearn-color-fitted-level-0: #f0f8ff;\n",
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" --sklearn-color-fitted-level-1: #d4ebff;\n",
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" --sklearn-color-fitted-level-2: #b3dbfd;\n",
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" --sklearn-color-fitted-level-3: cornflowerblue;\n",
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"\n",
|
|
" /* Specific color for light theme */\n",
|
|
" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
|
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" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
|
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" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
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" --sklearn-color-icon: #696969;\n",
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"\n",
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" @media (prefers-color-scheme: dark) {\n",
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" /* Redefinition of color scheme for dark theme */\n",
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" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
|
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" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
|
|
" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
|
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" --sklearn-color-icon: #878787;\n",
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" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 pre {\n",
|
|
" padding: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 input.sk-hidden--visually {\n",
|
|
" border: 0;\n",
|
|
" clip: rect(1px 1px 1px 1px);\n",
|
|
" clip: rect(1px, 1px, 1px, 1px);\n",
|
|
" height: 1px;\n",
|
|
" margin: -1px;\n",
|
|
" overflow: hidden;\n",
|
|
" padding: 0;\n",
|
|
" position: absolute;\n",
|
|
" width: 1px;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-dashed-wrapped {\n",
|
|
" border: 1px dashed var(--sklearn-color-line);\n",
|
|
" margin: 0 0.4em 0.5em 0.4em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" padding-bottom: 0.4em;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-container {\n",
|
|
" /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
|
|
" but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
|
|
" so we also need the `!important` here to be able to override the\n",
|
|
" default hidden behavior on the sphinx rendered scikit-learn.org.\n",
|
|
" See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
|
|
" display: inline-block !important;\n",
|
|
" position: relative;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-text-repr-fallback {\n",
|
|
" display: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"div.sk-parallel-item,\n",
|
|
"div.sk-serial,\n",
|
|
"div.sk-item {\n",
|
|
" /* draw centered vertical line to link estimators */\n",
|
|
" background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
|
|
" background-size: 2px 100%;\n",
|
|
" background-repeat: no-repeat;\n",
|
|
" background-position: center center;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Parallel-specific style estimator block */\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-parallel-item::after {\n",
|
|
" content: \"\";\n",
|
|
" width: 100%;\n",
|
|
" border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
|
|
" flex-grow: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-parallel {\n",
|
|
" display: flex;\n",
|
|
" align-items: stretch;\n",
|
|
" justify-content: center;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" position: relative;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-parallel-item {\n",
|
|
" display: flex;\n",
|
|
" flex-direction: column;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
|
|
" align-self: flex-end;\n",
|
|
" width: 50%;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
|
|
" align-self: flex-start;\n",
|
|
" width: 50%;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
|
|
" width: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Serial-specific style estimator block */\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-serial {\n",
|
|
" display: flex;\n",
|
|
" flex-direction: column;\n",
|
|
" align-items: center;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" padding-right: 1em;\n",
|
|
" padding-left: 1em;\n",
|
|
"}\n",
|
|
"\n",
|
|
"\n",
|
|
"/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
|
|
"clickable and can be expanded/collapsed.\n",
|
|
"- Pipeline and ColumnTransformer use this feature and define the default style\n",
|
|
"- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
|
|
"*/\n",
|
|
"\n",
|
|
"/* Pipeline and ColumnTransformer style (default) */\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-toggleable {\n",
|
|
" /* Default theme specific background. It is overwritten whether we have a\n",
|
|
" specific estimator or a Pipeline/ColumnTransformer */\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Toggleable label */\n",
|
|
"#sk-container-id-1 label.sk-toggleable__label {\n",
|
|
" cursor: pointer;\n",
|
|
" display: block;\n",
|
|
" width: 100%;\n",
|
|
" margin-bottom: 0;\n",
|
|
" padding: 0.5em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" text-align: center;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
|
|
" /* Arrow on the left of the label */\n",
|
|
" content: \"▸\";\n",
|
|
" float: left;\n",
|
|
" margin-right: 0.25em;\n",
|
|
" color: var(--sklearn-color-icon);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Toggleable content - dropdown */\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-toggleable__content {\n",
|
|
" max-height: 0;\n",
|
|
" max-width: 0;\n",
|
|
" overflow: hidden;\n",
|
|
" text-align: left;\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-toggleable__content pre {\n",
|
|
" margin: 0.2em;\n",
|
|
" border-radius: 0.25em;\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
|
|
" /* Expand drop-down */\n",
|
|
" max-height: 200px;\n",
|
|
" max-width: 100%;\n",
|
|
" overflow: auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
|
|
" content: \"▾\";\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Pipeline/ColumnTransformer-specific style */\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Estimator-specific style */\n",
|
|
"\n",
|
|
"/* Colorize estimator box */\n",
|
|
"#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
|
|
"#sk-container-id-1 div.sk-label label {\n",
|
|
" /* The background is the default theme color */\n",
|
|
" color: var(--sklearn-color-text-on-default-background);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* On hover, darken the color of the background */\n",
|
|
"#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Label box, darken color on hover, fitted */\n",
|
|
"#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Estimator label */\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-label label {\n",
|
|
" font-family: monospace;\n",
|
|
" font-weight: bold;\n",
|
|
" display: inline-block;\n",
|
|
" line-height: 1.2em;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-label-container {\n",
|
|
" text-align: center;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Estimator-specific */\n",
|
|
"#sk-container-id-1 div.sk-estimator {\n",
|
|
" font-family: monospace;\n",
|
|
" border: 1px dotted var(--sklearn-color-border-box);\n",
|
|
" border-radius: 0.25em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" margin-bottom: 0.5em;\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-estimator.fitted {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* on hover */\n",
|
|
"#sk-container-id-1 div.sk-estimator:hover {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
|
|
"\n",
|
|
"/* Common style for \"i\" and \"?\" */\n",
|
|
"\n",
|
|
".sk-estimator-doc-link,\n",
|
|
"a:link.sk-estimator-doc-link,\n",
|
|
"a:visited.sk-estimator-doc-link {\n",
|
|
" float: right;\n",
|
|
" font-size: smaller;\n",
|
|
" line-height: 1em;\n",
|
|
" font-family: monospace;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" border-radius: 1em;\n",
|
|
" height: 1em;\n",
|
|
" width: 1em;\n",
|
|
" text-decoration: none !important;\n",
|
|
" margin-left: 1ex;\n",
|
|
" /* unfitted */\n",
|
|
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
|
|
" color: var(--sklearn-color-unfitted-level-1);\n",
|
|
"}\n",
|
|
"\n",
|
|
".sk-estimator-doc-link.fitted,\n",
|
|
"a:link.sk-estimator-doc-link.fitted,\n",
|
|
"a:visited.sk-estimator-doc-link.fitted {\n",
|
|
" /* fitted */\n",
|
|
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
|
|
" color: var(--sklearn-color-fitted-level-1);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* On hover */\n",
|
|
"div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
|
|
".sk-estimator-doc-link:hover,\n",
|
|
"div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
|
|
".sk-estimator-doc-link:hover {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-3);\n",
|
|
" color: var(--sklearn-color-background);\n",
|
|
" text-decoration: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
|
|
".sk-estimator-doc-link.fitted:hover,\n",
|
|
"div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
|
|
".sk-estimator-doc-link.fitted:hover {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-3);\n",
|
|
" color: var(--sklearn-color-background);\n",
|
|
" text-decoration: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Span, style for the box shown on hovering the info icon */\n",
|
|
".sk-estimator-doc-link span {\n",
|
|
" display: none;\n",
|
|
" z-index: 9999;\n",
|
|
" position: relative;\n",
|
|
" font-weight: normal;\n",
|
|
" right: .2ex;\n",
|
|
" padding: .5ex;\n",
|
|
" margin: .5ex;\n",
|
|
" width: min-content;\n",
|
|
" min-width: 20ex;\n",
|
|
" max-width: 50ex;\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" box-shadow: 2pt 2pt 4pt #999;\n",
|
|
" /* unfitted */\n",
|
|
" background: var(--sklearn-color-unfitted-level-0);\n",
|
|
" border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
|
|
"}\n",
|
|
"\n",
|
|
".sk-estimator-doc-link.fitted span {\n",
|
|
" /* fitted */\n",
|
|
" background: var(--sklearn-color-fitted-level-0);\n",
|
|
" border: var(--sklearn-color-fitted-level-3);\n",
|
|
"}\n",
|
|
"\n",
|
|
".sk-estimator-doc-link:hover span {\n",
|
|
" display: block;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* \"?\"-specific style due to the `<a>` HTML tag */\n",
|
|
"\n",
|
|
"#sk-container-id-1 a.estimator_doc_link {\n",
|
|
" float: right;\n",
|
|
" font-size: 1rem;\n",
|
|
" line-height: 1em;\n",
|
|
" font-family: monospace;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" border-radius: 1rem;\n",
|
|
" height: 1rem;\n",
|
|
" width: 1rem;\n",
|
|
" text-decoration: none;\n",
|
|
" /* unfitted */\n",
|
|
" color: var(--sklearn-color-unfitted-level-1);\n",
|
|
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 a.estimator_doc_link.fitted {\n",
|
|
" /* fitted */\n",
|
|
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
|
|
" color: var(--sklearn-color-fitted-level-1);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* On hover */\n",
|
|
"#sk-container-id-1 a.estimator_doc_link:hover {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-3);\n",
|
|
" color: var(--sklearn-color-background);\n",
|
|
" text-decoration: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-3);\n",
|
|
"}\n",
|
|
"</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[('preprocessor',\n",
|
|
" ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler',\n",
|
|
" StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases',\n",
|
|
" 'total_amount',\n",
|
|
" 'nb_suppliers',\n",
|
|
" 'vente_internet_max',\n",
|
|
" 'purchase_date_min',\n",
|
|
" 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet',\n",
|
|
" 'fidelity', 'is_email_true',\n",
|
|
" 'opt_in', 'gender_female',\n",
|
|
" 'gender_male',\n",
|
|
" 'gender_other',\n",
|
|
" 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])),\n",
|
|
" ('logreg',\n",
|
|
" LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga'))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow \"> Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[('preprocessor',\n",
|
|
" ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler',\n",
|
|
" StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases',\n",
|
|
" 'total_amount',\n",
|
|
" 'nb_suppliers',\n",
|
|
" 'vente_internet_max',\n",
|
|
" 'purchase_date_min',\n",
|
|
" 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet',\n",
|
|
" 'fidelity', 'is_email_true',\n",
|
|
" 'opt_in', 'gender_female',\n",
|
|
" 'gender_male',\n",
|
|
" 'gender_other',\n",
|
|
" 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])),\n",
|
|
" ('logreg',\n",
|
|
" LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga'))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow \"> preprocessor: ColumnTransformer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for preprocessor: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content \"><pre>ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler', StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases', 'total_amount',\n",
|
|
" 'nb_suppliers', 'vente_internet_max',\n",
|
|
" 'purchase_date_min', 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet', 'fidelity',\n",
|
|
" 'is_email_true', 'opt_in', 'gender_female',\n",
|
|
" 'gender_male', 'gender_other', 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow \">num</label><div class=\"sk-toggleable__content \"><pre>['nb_tickets', 'nb_purchases', 'total_amount', 'nb_suppliers', 'vente_internet_max', 'purchase_date_min', 'purchase_date_max', 'time_between_purchase', 'nb_tickets_internet', 'fidelity', 'is_email_true', 'opt_in', 'gender_female', 'gender_male', 'gender_other', 'nb_campaigns', 'nb_campaigns_opened']</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow \"> StandardScaler<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content \"><pre>StandardScaler()</pre></div> </div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow \">cat</label><div class=\"sk-toggleable__content \"><pre>['opt_in']</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow \"> OneHotEncoder<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content \"><pre>OneHotEncoder(handle_unknown='ignore', sparse_output=False)</pre></div> </div></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow \"> LogisticRegression<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content \"><pre>LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga')</pre></div> </div></div></div></div></div></div>"
|
|
],
|
|
"text/plain": [
|
|
"Pipeline(steps=[('preprocessor',\n",
|
|
" ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler',\n",
|
|
" StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases',\n",
|
|
" 'total_amount',\n",
|
|
" 'nb_suppliers',\n",
|
|
" 'vente_internet_max',\n",
|
|
" 'purchase_date_min',\n",
|
|
" 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet',\n",
|
|
" 'fidelity', 'is_email_true',\n",
|
|
" 'opt_in', 'gender_female',\n",
|
|
" 'gender_male',\n",
|
|
" 'gender_other',\n",
|
|
" 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])),\n",
|
|
" ('logreg',\n",
|
|
" LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga'))])"
|
|
]
|
|
},
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Pipeline\n",
|
|
"pipeline = Pipeline(steps=[\n",
|
|
" ('preprocessor', preproc),\n",
|
|
" ('logreg', LogisticRegression(solver='saga', class_weight = weight_dict,\n",
|
|
" max_iter=5000)) \n",
|
|
"])\n",
|
|
"\n",
|
|
"pipeline.set_output(transform=\"pandas\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ed415f60-9663-4179-877b-233faf6e1645",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Baseline"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "2b467511-2ae5-4a16-a502-397c3460471d",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<style>#sk-container-id-2 {\n",
|
|
" /* Definition of color scheme common for light and dark mode */\n",
|
|
" --sklearn-color-text: black;\n",
|
|
" --sklearn-color-line: gray;\n",
|
|
" /* Definition of color scheme for unfitted estimators */\n",
|
|
" --sklearn-color-unfitted-level-0: #fff5e6;\n",
|
|
" --sklearn-color-unfitted-level-1: #f6e4d2;\n",
|
|
" --sklearn-color-unfitted-level-2: #ffe0b3;\n",
|
|
" --sklearn-color-unfitted-level-3: chocolate;\n",
|
|
" /* Definition of color scheme for fitted estimators */\n",
|
|
" --sklearn-color-fitted-level-0: #f0f8ff;\n",
|
|
" --sklearn-color-fitted-level-1: #d4ebff;\n",
|
|
" --sklearn-color-fitted-level-2: #b3dbfd;\n",
|
|
" --sklearn-color-fitted-level-3: cornflowerblue;\n",
|
|
"\n",
|
|
" /* Specific color for light theme */\n",
|
|
" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
|
|
" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
|
|
" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
|
|
" --sklearn-color-icon: #696969;\n",
|
|
"\n",
|
|
" @media (prefers-color-scheme: dark) {\n",
|
|
" /* Redefinition of color scheme for dark theme */\n",
|
|
" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
|
|
" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
|
|
" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
|
|
" --sklearn-color-icon: #878787;\n",
|
|
" }\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 pre {\n",
|
|
" padding: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 input.sk-hidden--visually {\n",
|
|
" border: 0;\n",
|
|
" clip: rect(1px 1px 1px 1px);\n",
|
|
" clip: rect(1px, 1px, 1px, 1px);\n",
|
|
" height: 1px;\n",
|
|
" margin: -1px;\n",
|
|
" overflow: hidden;\n",
|
|
" padding: 0;\n",
|
|
" position: absolute;\n",
|
|
" width: 1px;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-dashed-wrapped {\n",
|
|
" border: 1px dashed var(--sklearn-color-line);\n",
|
|
" margin: 0 0.4em 0.5em 0.4em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" padding-bottom: 0.4em;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-container {\n",
|
|
" /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
|
|
" but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
|
|
" so we also need the `!important` here to be able to override the\n",
|
|
" default hidden behavior on the sphinx rendered scikit-learn.org.\n",
|
|
" See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
|
|
" display: inline-block !important;\n",
|
|
" position: relative;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-text-repr-fallback {\n",
|
|
" display: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"div.sk-parallel-item,\n",
|
|
"div.sk-serial,\n",
|
|
"div.sk-item {\n",
|
|
" /* draw centered vertical line to link estimators */\n",
|
|
" background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
|
|
" background-size: 2px 100%;\n",
|
|
" background-repeat: no-repeat;\n",
|
|
" background-position: center center;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Parallel-specific style estimator block */\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-parallel-item::after {\n",
|
|
" content: \"\";\n",
|
|
" width: 100%;\n",
|
|
" border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
|
|
" flex-grow: 1;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-parallel {\n",
|
|
" display: flex;\n",
|
|
" align-items: stretch;\n",
|
|
" justify-content: center;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" position: relative;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-parallel-item {\n",
|
|
" display: flex;\n",
|
|
" flex-direction: column;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
|
|
" align-self: flex-end;\n",
|
|
" width: 50%;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
|
|
" align-self: flex-start;\n",
|
|
" width: 50%;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
|
|
" width: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Serial-specific style estimator block */\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-serial {\n",
|
|
" display: flex;\n",
|
|
" flex-direction: column;\n",
|
|
" align-items: center;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" padding-right: 1em;\n",
|
|
" padding-left: 1em;\n",
|
|
"}\n",
|
|
"\n",
|
|
"\n",
|
|
"/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
|
|
"clickable and can be expanded/collapsed.\n",
|
|
"- Pipeline and ColumnTransformer use this feature and define the default style\n",
|
|
"- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
|
|
"*/\n",
|
|
"\n",
|
|
"/* Pipeline and ColumnTransformer style (default) */\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-toggleable {\n",
|
|
" /* Default theme specific background. It is overwritten whether we have a\n",
|
|
" specific estimator or a Pipeline/ColumnTransformer */\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Toggleable label */\n",
|
|
"#sk-container-id-2 label.sk-toggleable__label {\n",
|
|
" cursor: pointer;\n",
|
|
" display: block;\n",
|
|
" width: 100%;\n",
|
|
" margin-bottom: 0;\n",
|
|
" padding: 0.5em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" text-align: center;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
|
|
" /* Arrow on the left of the label */\n",
|
|
" content: \"▸\";\n",
|
|
" float: left;\n",
|
|
" margin-right: 0.25em;\n",
|
|
" color: var(--sklearn-color-icon);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Toggleable content - dropdown */\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-toggleable__content {\n",
|
|
" max-height: 0;\n",
|
|
" max-width: 0;\n",
|
|
" overflow: hidden;\n",
|
|
" text-align: left;\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-toggleable__content pre {\n",
|
|
" margin: 0.2em;\n",
|
|
" border-radius: 0.25em;\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
|
|
" /* Expand drop-down */\n",
|
|
" max-height: 200px;\n",
|
|
" max-width: 100%;\n",
|
|
" overflow: auto;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
|
|
" content: \"▾\";\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Pipeline/ColumnTransformer-specific style */\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Estimator-specific style */\n",
|
|
"\n",
|
|
"/* Colorize estimator box */\n",
|
|
"#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
|
|
"#sk-container-id-2 div.sk-label label {\n",
|
|
" /* The background is the default theme color */\n",
|
|
" color: var(--sklearn-color-text-on-default-background);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* On hover, darken the color of the background */\n",
|
|
"#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Label box, darken color on hover, fitted */\n",
|
|
"#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Estimator label */\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-label label {\n",
|
|
" font-family: monospace;\n",
|
|
" font-weight: bold;\n",
|
|
" display: inline-block;\n",
|
|
" line-height: 1.2em;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-label-container {\n",
|
|
" text-align: center;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Estimator-specific */\n",
|
|
"#sk-container-id-2 div.sk-estimator {\n",
|
|
" font-family: monospace;\n",
|
|
" border: 1px dotted var(--sklearn-color-border-box);\n",
|
|
" border-radius: 0.25em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" margin-bottom: 0.5em;\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-estimator.fitted {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* on hover */\n",
|
|
"#sk-container-id-2 div.sk-estimator:hover {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
|
|
"\n",
|
|
"/* Common style for \"i\" and \"?\" */\n",
|
|
"\n",
|
|
".sk-estimator-doc-link,\n",
|
|
"a:link.sk-estimator-doc-link,\n",
|
|
"a:visited.sk-estimator-doc-link {\n",
|
|
" float: right;\n",
|
|
" font-size: smaller;\n",
|
|
" line-height: 1em;\n",
|
|
" font-family: monospace;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" border-radius: 1em;\n",
|
|
" height: 1em;\n",
|
|
" width: 1em;\n",
|
|
" text-decoration: none !important;\n",
|
|
" margin-left: 1ex;\n",
|
|
" /* unfitted */\n",
|
|
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
|
|
" color: var(--sklearn-color-unfitted-level-1);\n",
|
|
"}\n",
|
|
"\n",
|
|
".sk-estimator-doc-link.fitted,\n",
|
|
"a:link.sk-estimator-doc-link.fitted,\n",
|
|
"a:visited.sk-estimator-doc-link.fitted {\n",
|
|
" /* fitted */\n",
|
|
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
|
|
" color: var(--sklearn-color-fitted-level-1);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* On hover */\n",
|
|
"div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
|
|
".sk-estimator-doc-link:hover,\n",
|
|
"div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
|
|
".sk-estimator-doc-link:hover {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-3);\n",
|
|
" color: var(--sklearn-color-background);\n",
|
|
" text-decoration: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
|
|
".sk-estimator-doc-link.fitted:hover,\n",
|
|
"div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
|
|
".sk-estimator-doc-link.fitted:hover {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-3);\n",
|
|
" color: var(--sklearn-color-background);\n",
|
|
" text-decoration: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Span, style for the box shown on hovering the info icon */\n",
|
|
".sk-estimator-doc-link span {\n",
|
|
" display: none;\n",
|
|
" z-index: 9999;\n",
|
|
" position: relative;\n",
|
|
" font-weight: normal;\n",
|
|
" right: .2ex;\n",
|
|
" padding: .5ex;\n",
|
|
" margin: .5ex;\n",
|
|
" width: min-content;\n",
|
|
" min-width: 20ex;\n",
|
|
" max-width: 50ex;\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
" box-shadow: 2pt 2pt 4pt #999;\n",
|
|
" /* unfitted */\n",
|
|
" background: var(--sklearn-color-unfitted-level-0);\n",
|
|
" border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
|
|
"}\n",
|
|
"\n",
|
|
".sk-estimator-doc-link.fitted span {\n",
|
|
" /* fitted */\n",
|
|
" background: var(--sklearn-color-fitted-level-0);\n",
|
|
" border: var(--sklearn-color-fitted-level-3);\n",
|
|
"}\n",
|
|
"\n",
|
|
".sk-estimator-doc-link:hover span {\n",
|
|
" display: block;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* \"?\"-specific style due to the `<a>` HTML tag */\n",
|
|
"\n",
|
|
"#sk-container-id-2 a.estimator_doc_link {\n",
|
|
" float: right;\n",
|
|
" font-size: 1rem;\n",
|
|
" line-height: 1em;\n",
|
|
" font-family: monospace;\n",
|
|
" background-color: var(--sklearn-color-background);\n",
|
|
" border-radius: 1rem;\n",
|
|
" height: 1rem;\n",
|
|
" width: 1rem;\n",
|
|
" text-decoration: none;\n",
|
|
" /* unfitted */\n",
|
|
" color: var(--sklearn-color-unfitted-level-1);\n",
|
|
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 a.estimator_doc_link.fitted {\n",
|
|
" /* fitted */\n",
|
|
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
|
|
" color: var(--sklearn-color-fitted-level-1);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* On hover */\n",
|
|
"#sk-container-id-2 a.estimator_doc_link:hover {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-3);\n",
|
|
" color: var(--sklearn-color-background);\n",
|
|
" text-decoration: none;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-3);\n",
|
|
"}\n",
|
|
"</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[('preprocessor',\n",
|
|
" ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler',\n",
|
|
" StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases',\n",
|
|
" 'total_amount',\n",
|
|
" 'nb_suppliers',\n",
|
|
" 'vente_internet_max',\n",
|
|
" 'purchase_date_min',\n",
|
|
" 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet',\n",
|
|
" 'fidelity', 'is_email_true',\n",
|
|
" 'opt_in', 'gender_female',\n",
|
|
" 'gender_male',\n",
|
|
" 'gender_other',\n",
|
|
" 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])),\n",
|
|
" ('logreg',\n",
|
|
" LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga'))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[('preprocessor',\n",
|
|
" ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler',\n",
|
|
" StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases',\n",
|
|
" 'total_amount',\n",
|
|
" 'nb_suppliers',\n",
|
|
" 'vente_internet_max',\n",
|
|
" 'purchase_date_min',\n",
|
|
" 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet',\n",
|
|
" 'fidelity', 'is_email_true',\n",
|
|
" 'opt_in', 'gender_female',\n",
|
|
" 'gender_male',\n",
|
|
" 'gender_other',\n",
|
|
" 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])),\n",
|
|
" ('logreg',\n",
|
|
" LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga'))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> preprocessor: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for preprocessor: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler', StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases', 'total_amount',\n",
|
|
" 'nb_suppliers', 'vente_internet_max',\n",
|
|
" 'purchase_date_min', 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet', 'fidelity',\n",
|
|
" 'is_email_true', 'opt_in', 'gender_female',\n",
|
|
" 'gender_male', 'gender_other', 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">num</label><div class=\"sk-toggleable__content fitted\"><pre>['nb_tickets', 'nb_purchases', 'total_amount', 'nb_suppliers', 'vente_internet_max', 'purchase_date_min', 'purchase_date_max', 'time_between_purchase', 'nb_tickets_internet', 'fidelity', 'is_email_true', 'opt_in', 'gender_female', 'gender_male', 'gender_other', 'nb_campaigns', 'nb_campaigns_opened']</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" ><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-12\" type=\"checkbox\" ><label for=\"sk-estimator-id-12\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">cat</label><div class=\"sk-toggleable__content fitted\"><pre>['opt_in']</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-13\" type=\"checkbox\" ><label for=\"sk-estimator-id-13\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(handle_unknown='ignore', sparse_output=False)</pre></div> </div></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" ><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga')</pre></div> </div></div></div></div></div></div>"
|
|
],
|
|
"text/plain": [
|
|
"Pipeline(steps=[('preprocessor',\n",
|
|
" ColumnTransformer(transformers=[('num',\n",
|
|
" Pipeline(steps=[('scaler',\n",
|
|
" StandardScaler())]),\n",
|
|
" ['nb_tickets', 'nb_purchases',\n",
|
|
" 'total_amount',\n",
|
|
" 'nb_suppliers',\n",
|
|
" 'vente_internet_max',\n",
|
|
" 'purchase_date_min',\n",
|
|
" 'purchase_date_max',\n",
|
|
" 'time_between_purchase',\n",
|
|
" 'nb_tickets_internet',\n",
|
|
" 'fidelity', 'is_email_true',\n",
|
|
" 'opt_in', 'gender_female',\n",
|
|
" 'gender_male',\n",
|
|
" 'gender_other',\n",
|
|
" 'nb_campaigns',\n",
|
|
" 'nb_campaigns_opened']),\n",
|
|
" ('cat',\n",
|
|
" Pipeline(steps=[('onehot',\n",
|
|
" OneHotEncoder(handle_unknown='ignore',\n",
|
|
" sparse_output=False))]),\n",
|
|
" ['opt_in'])])),\n",
|
|
" ('logreg',\n",
|
|
" LogisticRegression(class_weight={0.0: 0.5837086520288036,\n",
|
|
" 1.0: 3.486549107420539},\n",
|
|
" max_iter=5000, solver='saga'))])"
|
|
]
|
|
},
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"pipeline.fit(X_train, y_train)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"id": "6356e870-0dfc-4e60-9e48-e2de5e7f9f87",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Accuracy Score: 0.7829358141858141\n",
|
|
"F1 Score: 0.5016842256145632\n",
|
|
"Recall Score: 0.7669831994156319\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"y_pred = pipeline.predict(X_test)\n",
|
|
"\n",
|
|
"# Calculate the F1 score\n",
|
|
"acc = accuracy_score(y_test, y_pred)\n",
|
|
"print(f\"Accuracy Score: {acc}\")\n",
|
|
"\n",
|
|
"f1 = f1_score(y_test, y_pred)\n",
|
|
"print(f\"F1 Score: {f1}\")\n",
|
|
"\n",
|
|
"recall = recall_score(y_test, y_pred)\n",
|
|
"print(f\"Recall Score: {recall}\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"id": "09387a09-0d53-4c54-baac-f3c2a57a629a",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"draw_confusion_matrix(y_test, y_pred)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"id": "580b58d7-596f-4207-8c99-4365aba2bc9f",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1400x800 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"draw_roc_curve(X_test, y_test)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"id": "ca5d0a55-adbb-47a0-a4c8-6af9ca75ca9d",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"draw_features_importance(pipeline, 'logreg')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"id": "f3782ec2-9f2c-4c23-9691-79413c4e04be",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"draw_prob_distribution(X_test)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ae8e9bd3-0f6a-4f82-bb4c-470cbdc8d6bb",
|
|
"metadata": {
|
|
"jp-MarkdownHeadingCollapsed": true
|
|
},
|
|
"source": [
|
|
"## Cross Validation"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"id": "7f0535de-34f1-4e97-b993-b429ecf0a554",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"y_train = y_train['y_has_purchased']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"id": "f7fca463-d7d6-493b-8329-fdfa92457f78",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Best parameters found: {'logreg__C': 0.0009765625, 'logreg__class_weight': 'balanced', 'logreg__penalty': 'l1'}\n",
|
|
"Best cross-validation score: 0.65\n",
|
|
"Test set score: 0.64\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Cross validation\n",
|
|
"\n",
|
|
"grid_search = GridSearchCV(pipeline, param_grid, cv=3, scoring=recall_scorer, error_score='raise',\n",
|
|
" n_jobs=-1)\n",
|
|
"\n",
|
|
"grid_search.fit(X_train, y_train)\n",
|
|
"\n",
|
|
"# Print the best parameters and the best score\n",
|
|
"print(\"Best parameters found: \", grid_search.best_params_)\n",
|
|
"print(\"Best cross-validation score: {:.2f}\".format(grid_search.best_score_))\n",
|
|
"\n",
|
|
"# Evaluate the best model on the test set\n",
|
|
"test_score = grid_search.score(X_test, y_test)\n",
|
|
"print(\"Test set score: {:.2f}\".format(test_score))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 43,
|
|
"id": "56bd7828-4de1-4166-bea0-5d5e152b9d38",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"y_pred = grid_search.predict(X_test)\n",
|
|
"\n",
|
|
"draw_confusion_matrix(y_test, y_pred)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 44,
|
|
"id": "319fe0eb-4d4a-492c-bd50-3f08ab483021",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1400x800 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"draw_roc_curve(X_test, y_test)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ab122f66-1591-43ea-a364-2564f09b2bb3",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Segmentation du score de prédiction"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 61,
|
|
"id": "279e18c7-29d8-4328-963a-18babd13c2c8",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"coefficients = pipeline.named_steps['logreg'].coef_[0]\n",
|
|
"feature_names = pipeline.named_steps['logreg'].feature_names_in_\n",
|
|
"\n",
|
|
"# Tracer l'importance des caractéristiques\n",
|
|
"plt.figure(figsize=(10, 6))\n",
|
|
"plt.barh(feature_names, coefficients, color='skyblue')\n",
|
|
"plt.xlabel('Importance des caractéristiques')\n",
|
|
"plt.ylabel('Caractéristiques')\n",
|
|
"plt.title('Importance des caractéristiques dans le modèle de régression logistique')\n",
|
|
"plt.grid(True)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 70,
|
|
"id": "210b931c-6d46-4ebf-a9c7-d1ee05c3fadf",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Création d'un dataframe avec le score\n",
|
|
"dataset_for_segmentation = dataset_test[['customer_id'] + numeric_features + categorical_features]\n",
|
|
"\n",
|
|
"y_predict_proba = pipeline.predict_proba(X_test)[:, 1]\n",
|
|
"\n",
|
|
"dataset_for_segmentation['prediction_probability'] = y_predict_proba\n",
|
|
"\n",
|
|
"# Arrondir les valeurs de la colonne 'prediction_probability' et les multiplier par 10\n",
|
|
"dataset_for_segmentation['category'] = dataset_for_segmentation['prediction_probability'].apply(lambda x: int(x * 10))\n",
|
|
"\n",
|
|
"dataset_for_segmentation['prediction'] = y_pred\n",
|
|
"\n",
|
|
"def premiere_partie(chaine):\n",
|
|
" if chaine:\n",
|
|
" return chaine.split('_')[0]\n",
|
|
" else:\n",
|
|
" return None\n",
|
|
"\n",
|
|
"dataset_for_segmentation['company_number'] = dataset_for_segmentation['customer_id'].apply(lambda x: premiere_partie(x))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "055e47dd-9ff3-4853-a46d-d5a5edc1f361",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 73,
|
|
"id": "969f1f92-d715-4d74-85a7-437e72838cb5",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
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"<div>\n",
|
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"<style scoped>\n",
|
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" .dataframe tbody tr th:only-of-type {\n",
|
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" vertical-align: middle;\n",
|
|
" }\n",
|
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"\n",
|
|
" .dataframe tbody tr th {\n",
|
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" vertical-align: top;\n",
|
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" }\n",
|
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"\n",
|
|
" .dataframe thead tr th {\n",
|
|
" text-align: left;\n",
|
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" }\n",
|
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"\n",
|
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" .dataframe thead tr:last-of-type th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr>\n",
|
|
" <th></th>\n",
|
|
" <th>nb_tickets</th>\n",
|
|
" <th>nb_purchases</th>\n",
|
|
" <th>total_amount</th>\n",
|
|
" <th>nb_suppliers</th>\n",
|
|
" <th>vente_internet_max</th>\n",
|
|
" <th>purchase_date_min</th>\n",
|
|
" <th>purchase_date_max</th>\n",
|
|
" <th>time_between_purchase</th>\n",
|
|
" <th>nb_tickets_internet</th>\n",
|
|
" <th>fidelity</th>\n",
|
|
" <th>gender_female</th>\n",
|
|
" <th>gender_male</th>\n",
|
|
" <th>gender_other</th>\n",
|
|
" <th>nb_campaigns</th>\n",
|
|
" <th>nb_campaigns_opened</th>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th></th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" <th>mean</th>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>category</th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>0.113637</td>\n",
|
|
" <td>0.006274</td>\n",
|
|
" <td>1.586366</td>\n",
|
|
" <td>0.005821</td>\n",
|
|
" <td>0.000647</td>\n",
|
|
" <td>548.790455</td>\n",
|
|
" <td>548.773103</td>\n",
|
|
" <td>-0.977118</td>\n",
|
|
" <td>0.001585</td>\n",
|
|
" <td>0.000776</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000032</td>\n",
|
|
" <td>0.999968</td>\n",
|
|
" <td>13.984219</td>\n",
|
|
" <td>1.302720</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>0.810841</td>\n",
|
|
" <td>0.128432</td>\n",
|
|
" <td>9.611292</td>\n",
|
|
" <td>0.125295</td>\n",
|
|
" <td>0.018186</td>\n",
|
|
" <td>525.437516</td>\n",
|
|
" <td>525.275222</td>\n",
|
|
" <td>-0.729328</td>\n",
|
|
" <td>0.054312</td>\n",
|
|
" <td>0.111832</td>\n",
|
|
" <td>0.245480</td>\n",
|
|
" <td>0.495929</td>\n",
|
|
" <td>0.258591</td>\n",
|
|
" <td>18.413562</td>\n",
|
|
" <td>3.718711</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>1.159419</td>\n",
|
|
" <td>0.339253</td>\n",
|
|
" <td>15.182143</td>\n",
|
|
" <td>0.337577</td>\n",
|
|
" <td>0.323824</td>\n",
|
|
" <td>501.529129</td>\n",
|
|
" <td>501.415505</td>\n",
|
|
" <td>-0.554439</td>\n",
|
|
" <td>0.969939</td>\n",
|
|
" <td>0.304757</td>\n",
|
|
" <td>0.392570</td>\n",
|
|
" <td>0.297258</td>\n",
|
|
" <td>0.310173</td>\n",
|
|
" <td>17.395042</td>\n",
|
|
" <td>2.608084</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>2.153080</td>\n",
|
|
" <td>0.744161</td>\n",
|
|
" <td>27.820044</td>\n",
|
|
" <td>0.734881</td>\n",
|
|
" <td>0.600982</td>\n",
|
|
" <td>287.051054</td>\n",
|
|
" <td>286.675385</td>\n",
|
|
" <td>0.105360</td>\n",
|
|
" <td>1.776035</td>\n",
|
|
" <td>0.659878</td>\n",
|
|
" <td>0.288813</td>\n",
|
|
" <td>0.253244</td>\n",
|
|
" <td>0.457943</td>\n",
|
|
" <td>16.790421</td>\n",
|
|
" <td>4.173954</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>2.044749</td>\n",
|
|
" <td>0.777640</td>\n",
|
|
" <td>27.353145</td>\n",
|
|
" <td>0.754549</td>\n",
|
|
" <td>0.079213</td>\n",
|
|
" <td>297.179255</td>\n",
|
|
" <td>295.019902</td>\n",
|
|
" <td>1.898178</td>\n",
|
|
" <td>0.293760</td>\n",
|
|
" <td>0.894877</td>\n",
|
|
" <td>0.666980</td>\n",
|
|
" <td>0.301424</td>\n",
|
|
" <td>0.031596</td>\n",
|
|
" <td>16.954707</td>\n",
|
|
" <td>6.060621</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>3.237988</td>\n",
|
|
" <td>0.958520</td>\n",
|
|
" <td>46.637380</td>\n",
|
|
" <td>0.807655</td>\n",
|
|
" <td>0.484785</td>\n",
|
|
" <td>387.464785</td>\n",
|
|
" <td>380.145068</td>\n",
|
|
" <td>7.111357</td>\n",
|
|
" <td>2.080397</td>\n",
|
|
" <td>1.164958</td>\n",
|
|
" <td>0.497758</td>\n",
|
|
" <td>0.259769</td>\n",
|
|
" <td>0.242473</td>\n",
|
|
" <td>27.006406</td>\n",
|
|
" <td>12.457719</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>3.592233</td>\n",
|
|
" <td>1.102881</td>\n",
|
|
" <td>49.989226</td>\n",
|
|
" <td>0.878014</td>\n",
|
|
" <td>0.599906</td>\n",
|
|
" <td>268.627019</td>\n",
|
|
" <td>250.949344</td>\n",
|
|
" <td>17.539247</td>\n",
|
|
" <td>2.525994</td>\n",
|
|
" <td>1.420921</td>\n",
|
|
" <td>0.534607</td>\n",
|
|
" <td>0.304259</td>\n",
|
|
" <td>0.161134</td>\n",
|
|
" <td>14.073285</td>\n",
|
|
" <td>4.604134</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>3.747016</td>\n",
|
|
" <td>1.391266</td>\n",
|
|
" <td>40.710335</td>\n",
|
|
" <td>0.914702</td>\n",
|
|
" <td>0.160990</td>\n",
|
|
" <td>309.716173</td>\n",
|
|
" <td>274.795570</td>\n",
|
|
" <td>34.796876</td>\n",
|
|
" <td>0.844250</td>\n",
|
|
" <td>1.963028</td>\n",
|
|
" <td>0.650364</td>\n",
|
|
" <td>0.263464</td>\n",
|
|
" <td>0.086172</td>\n",
|
|
" <td>26.186317</td>\n",
|
|
" <td>8.891703</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>5.698276</td>\n",
|
|
" <td>1.567006</td>\n",
|
|
" <td>63.033699</td>\n",
|
|
" <td>0.907915</td>\n",
|
|
" <td>0.334248</td>\n",
|
|
" <td>326.485952</td>\n",
|
|
" <td>257.940194</td>\n",
|
|
" <td>68.425460</td>\n",
|
|
" <td>2.794279</td>\n",
|
|
" <td>2.413009</td>\n",
|
|
" <td>0.606583</td>\n",
|
|
" <td>0.251567</td>\n",
|
|
" <td>0.141850</td>\n",
|
|
" <td>30.987461</td>\n",
|
|
" <td>11.676332</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>14.505956</td>\n",
|
|
" <td>3.211571</td>\n",
|
|
" <td>107.288514</td>\n",
|
|
" <td>1.011628</td>\n",
|
|
" <td>0.157119</td>\n",
|
|
" <td>369.696066</td>\n",
|
|
" <td>209.280306</td>\n",
|
|
" <td>160.348544</td>\n",
|
|
" <td>3.514464</td>\n",
|
|
" <td>5.394498</td>\n",
|
|
" <td>0.669314</td>\n",
|
|
" <td>0.223766</td>\n",
|
|
" <td>0.106920</td>\n",
|
|
" <td>45.928247</td>\n",
|
|
" <td>18.241634</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>2262.859155</td>\n",
|
|
" <td>45.619718</td>\n",
|
|
" <td>11051.732394</td>\n",
|
|
" <td>1.464789</td>\n",
|
|
" <td>0.154930</td>\n",
|
|
" <td>467.111875</td>\n",
|
|
" <td>31.146796</td>\n",
|
|
" <td>435.950994</td>\n",
|
|
" <td>54.295775</td>\n",
|
|
" <td>64.704225</td>\n",
|
|
" <td>0.507042</td>\n",
|
|
" <td>0.295775</td>\n",
|
|
" <td>0.197183</td>\n",
|
|
" <td>53.352113</td>\n",
|
|
" <td>26.070423</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" nb_tickets nb_purchases total_amount nb_suppliers \\\n",
|
|
" mean mean mean mean \n",
|
|
"category \n",
|
|
"0 0.113637 0.006274 1.586366 0.005821 \n",
|
|
"1 0.810841 0.128432 9.611292 0.125295 \n",
|
|
"2 1.159419 0.339253 15.182143 0.337577 \n",
|
|
"3 2.153080 0.744161 27.820044 0.734881 \n",
|
|
"4 2.044749 0.777640 27.353145 0.754549 \n",
|
|
"5 3.237988 0.958520 46.637380 0.807655 \n",
|
|
"6 3.592233 1.102881 49.989226 0.878014 \n",
|
|
"7 3.747016 1.391266 40.710335 0.914702 \n",
|
|
"8 5.698276 1.567006 63.033699 0.907915 \n",
|
|
"9 14.505956 3.211571 107.288514 1.011628 \n",
|
|
"10 2262.859155 45.619718 11051.732394 1.464789 \n",
|
|
"\n",
|
|
" vente_internet_max purchase_date_min purchase_date_max \\\n",
|
|
" mean mean mean \n",
|
|
"category \n",
|
|
"0 0.000647 548.790455 548.773103 \n",
|
|
"1 0.018186 525.437516 525.275222 \n",
|
|
"2 0.323824 501.529129 501.415505 \n",
|
|
"3 0.600982 287.051054 286.675385 \n",
|
|
"4 0.079213 297.179255 295.019902 \n",
|
|
"5 0.484785 387.464785 380.145068 \n",
|
|
"6 0.599906 268.627019 250.949344 \n",
|
|
"7 0.160990 309.716173 274.795570 \n",
|
|
"8 0.334248 326.485952 257.940194 \n",
|
|
"9 0.157119 369.696066 209.280306 \n",
|
|
"10 0.154930 467.111875 31.146796 \n",
|
|
"\n",
|
|
" time_between_purchase nb_tickets_internet fidelity gender_female \\\n",
|
|
" mean mean mean mean \n",
|
|
"category \n",
|
|
"0 -0.977118 0.001585 0.000776 0.000000 \n",
|
|
"1 -0.729328 0.054312 0.111832 0.245480 \n",
|
|
"2 -0.554439 0.969939 0.304757 0.392570 \n",
|
|
"3 0.105360 1.776035 0.659878 0.288813 \n",
|
|
"4 1.898178 0.293760 0.894877 0.666980 \n",
|
|
"5 7.111357 2.080397 1.164958 0.497758 \n",
|
|
"6 17.539247 2.525994 1.420921 0.534607 \n",
|
|
"7 34.796876 0.844250 1.963028 0.650364 \n",
|
|
"8 68.425460 2.794279 2.413009 0.606583 \n",
|
|
"9 160.348544 3.514464 5.394498 0.669314 \n",
|
|
"10 435.950994 54.295775 64.704225 0.507042 \n",
|
|
"\n",
|
|
" gender_male gender_other nb_campaigns nb_campaigns_opened \n",
|
|
" mean mean mean mean \n",
|
|
"category \n",
|
|
"0 0.000032 0.999968 13.984219 1.302720 \n",
|
|
"1 0.495929 0.258591 18.413562 3.718711 \n",
|
|
"2 0.297258 0.310173 17.395042 2.608084 \n",
|
|
"3 0.253244 0.457943 16.790421 4.173954 \n",
|
|
"4 0.301424 0.031596 16.954707 6.060621 \n",
|
|
"5 0.259769 0.242473 27.006406 12.457719 \n",
|
|
"6 0.304259 0.161134 14.073285 4.604134 \n",
|
|
"7 0.263464 0.086172 26.186317 8.891703 \n",
|
|
"8 0.251567 0.141850 30.987461 11.676332 \n",
|
|
"9 0.223766 0.106920 45.928247 18.241634 \n",
|
|
"10 0.295775 0.197183 53.352113 26.070423 "
|
|
]
|
|
},
|
|
"execution_count": 73,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Grouper le DataFrame par la colonne 'category' et calculer la moyenne pour chaque groupe\n",
|
|
"summary_stats = dataset_for_segmentation.groupby('category')[numeric_features].describe()\n",
|
|
"\n",
|
|
"# Sélectionner uniquement la colonne 'mean' pour chaque variable numérique\n",
|
|
"mean_stats = summary_stats.loc[:, (slice(None), 'mean')]\n",
|
|
"\n",
|
|
"# Afficher le DataFrame résultant\n",
|
|
"mean_stats"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 75,
|
|
"id": "14da601e-7b1b-469c-bab1-de8fad4047f2",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x600 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Plot histogram\n",
|
|
"plt.figure(figsize=(8, 6))\n",
|
|
"plt.hist(y_predict_proba, bins=10, range=(0, 1), color='blue', alpha=0.7)\n",
|
|
"\n",
|
|
"# Réglage des limites des axes x et y\n",
|
|
"plt.xlim(0, 1)\n",
|
|
"plt.ylim(0, None) # Laissez le maximum sur l'axe y pour s'ajuster automatiquement\n",
|
|
"\n",
|
|
"plt.title('Histogramme des probabilités pour la classe 1')\n",
|
|
"plt.xlabel('Probabilité')\n",
|
|
"plt.ylabel('Fréquence')\n",
|
|
"plt.grid(True)\n",
|
|
"plt.show()\n"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.11.6"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|