g_series_8.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta,date\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "from sklearn.metrics import classification_report,confusion_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from __future__ import division\n",
    "from sklearn.cluster import KMeans\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.plotly as py\n",
    "import plotly.offline as pyoff\n",
    "import plotly.graph_objs as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn\n",
    "import xgboost as xgb\n",
    "from sklearn.model_selection import KFold, cross_val_score, train_test_split\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        define('plotly', function(require, exports, module) {\n",
       "            /**\n",
       "* plotly.js v1.47.3\n",
       "* Copyright 2012-2019, Plotly, Inc.\n",
       "* All rights reserved.\n",
       "* Licensed under the MIT license\n",
       "*/\n",

Great job! Thanks for sharing the notebook! was wondering if you could share the dataset you used for this analysis?

Thanks

https://gist.github.com/karamanbk/ef1a118592e2f7954e5bb582e09bdde3

It is also here:
https://www.kaggle.com/davinwijaya/customer-retention

You did a great job! But I would like to ask how to evaluate the uplift model, AUC，AUUC，Qini or other else? Thank you for you reply