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shap_example.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "shap_example.ipynb",
"provenance": [],
"collapsed_sections": [],
"mount_file_id": "1HS8PBZ7rUGwhlyT-Pni0ri0uVA0TqRyi",
"authorship_tag": "ABX9TyOE0eW40Ey3b4yJvh8LFRZC",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/nogawanogawa/608c56b4b881eafe8e40ada50e9367b2/shap_example.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "4Er6TN4Qq3He",
"outputId": "0322645b-c3df-4c02-f2cf-7823484b735b"
},
"source": [
"!pip install shap\n",
"!pip install econml\n",
"!pip install -U scikit-learn\n",
"\n",
"# ランタイム再起動の支持が出るので再起動"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": [
"Requirement already satisfied: shap in /usr/local/lib/python3.7/dist-packages (0.38.1)\n",
"Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from shap) (1.1.5)\n",
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"Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->shap) (2018.9)\n",
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"Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from numba->shap) (57.2.0)\n",
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"Requirement already satisfied: shap~=0.38.1 in /usr/local/lib/python3.7/dist-packages (from econml) (0.38.1)\n",
"Requirement already satisfied: dowhy in /usr/local/lib/python3.7/dist-packages (from econml) (0.6)\n",
"Requirement already satisfied: scikit-learn>0.22.0 in /usr/local/lib/python3.7/dist-packages (from econml) (0.24.2)\n",
"Requirement already satisfied: lightgbm in /usr/local/lib/python3.7/dist-packages (from econml) (2.2.3)\n",
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"Requirement already satisfied: tqdm>4.25.0 in /usr/local/lib/python3.7/dist-packages (from shap~=0.38.1->econml) (4.41.1)\n",
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"Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from numba!=0.42.1->econml) (57.2.0)\n",
"Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from patsy>=0.4.0->statsmodels>=0.10->econml) (1.15.0)\n",
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"Requirement already satisfied: pyparsing>=2.1.4 in /usr/local/lib/python3.7/dist-packages (from pydot>=1.4->dowhy->econml) (2.4.7)\n",
"Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.7/dist-packages (from sympy>=1.4->dowhy->econml) (1.2.1)\n",
"Requirement already up-to-date: scikit-learn in /usr/local/lib/python3.7/dist-packages (0.24.2)\n",
"Requirement already satisfied, skipping upgrade: threadpoolctl>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn) (2.2.0)\n",
"Requirement already satisfied, skipping upgrade: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn) (1.0.1)\n",
"Requirement already satisfied, skipping upgrade: numpy>=1.13.3 in /usr/local/lib/python3.7/dist-packages (from scikit-learn) (1.19.5)\n",
"Requirement already satisfied, skipping upgrade: scipy>=0.19.1 in /usr/local/lib/python3.7/dist-packages (from scikit-learn) (1.4.1)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ukzzJPldqoFo"
},
"source": [
"# This cell defines the functions we use to generate the data in our scenario\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import scipy.stats\n",
"import sklearn\n",
"import xgboost\n",
"import matplotlib.pyplot as plt\n",
"\n",
"class FixableDataFrame(pd.DataFrame):\n",
" \"\"\" Helper class for manipulating generative models.\n",
" \"\"\"\n",
" def __init__(self, *args, fixed={}, **kwargs):\n",
" self.__dict__[\"__fixed_var_dictionary\"] = fixed\n",
" super(FixableDataFrame, self).__init__(*args, **kwargs)\n",
" def __setitem__(self, key, value):\n",
" out = super(FixableDataFrame, self).__setitem__(key, value)\n",
" if isinstance(key, str) and key in self.__dict__[\"__fixed_var_dictionary\"]:\n",
" out = super(FixableDataFrame, self).__setitem__(key, self.__dict__[\"__fixed_var_dictionary\"][key])\n",
" return out\n",
"\n",
"# generate the data\n",
"def generator(n, fixed={}, seed=0):\n",
" \"\"\" The generative model for our subscriber retention example.\n",
" \"\"\"\n",
" if seed is not None:\n",
" np.random.seed(seed)\n",
" X = FixableDataFrame(fixed=fixed)\n",
"\n",
" # the number of sales calls made to this customer\n",
" X[\"Sales calls\"] = np.random.uniform(0, 4, size=(n,)).round()\n",
"\n",
" # the number of sales calls made to this customer\n",
" X[\"Interactions\"] = X[\"Sales calls\"] + np.random.poisson(0.2, size=(n,))\n",
"\n",
" # the health of the regional economy this customer is a part of\n",
" X[\"Economy\"] = np.random.uniform(0, 1, size=(n,))\n",
"\n",
" # the time since the last product upgrade when this customer came up for renewal\n",
" X[\"Last upgrade\"] = np.random.uniform(0, 20, size=(n,))\n",
"\n",
" # how much the user perceives that they need the product\n",
" X[\"Product need\"] = (X[\"Sales calls\"] * 0.1 + np.random.normal(0, 1, size=(n,)))\n",
"\n",
" # the fractional discount offered to this customer upon renewal\n",
" X[\"Discount\"] = ((1-scipy.special.expit(X[\"Product need\"])) * 0.5 + 0.5 * np.random.uniform(0, 1, size=(n,))) / 2\n",
"\n",
" # What percent of the days in the last period was the user actively using the product\n",
" X[\"Monthly usage\"] = scipy.special.expit(X[\"Product need\"] * 0.3 + np.random.normal(0, 1, size=(n,)))\n",
"\n",
" # how much ad money we spent per user targeted at this user (or a group this user is in)\n",
" X[\"Ad spend\"] = X[\"Monthly usage\"] * np.random.uniform(0.99, 0.9, size=(n,)) + (X[\"Last upgrade\"] < 1) + (X[\"Last upgrade\"] < 2)\n",
"\n",
" # how many bugs did this user encounter in the since their last renewal\n",
" X[\"Bugs faced\"] = np.array([np.random.poisson(v*2) for v in X[\"Monthly usage\"]])\n",
"\n",
" # how many bugs did the user report?\n",
" X[\"Bugs reported\"] = (X[\"Bugs faced\"] * scipy.special.expit(X[\"Product need\"])).round()\n",
"\n",
" # did the user renew?\n",
" X[\"Did renew\"] = scipy.special.expit(7 * (\n",
" 0.18 * X[\"Product need\"] \\\n",
" + 0.08 * X[\"Monthly usage\"] \\\n",
" + 0.1 * X[\"Economy\"] \\\n",
" + 0.05 * X[\"Discount\"] \\\n",
" + 0.05 * np.random.normal(0, 1, size=(n,)) \\\n",
" + 0.05 * (1 - X['Bugs faced'] / 20) \\\n",
" + 0.005 * X[\"Sales calls\"] \\\n",
" + 0.015 * X[\"Interactions\"] \\\n",
" + 0.1 / (X[\"Last upgrade\"]/4 + 0.25)\n",
" + X[\"Ad spend\"] * 0.0 - 0.45\n",
" ))\n",
"\n",
" # in real life we would make a random draw to get either 0 or 1 for if the\n",
" # customer did or did not renew. but here we leave the label as the probability\n",
" # so that we can get less noise in our plots. Uncomment this line to get\n",
" # noiser causal effect lines but the same basic results\n",
" X[\"Did renew\"] = scipy.stats.bernoulli.rvs(X[\"Did renew\"])\n",
"\n",
" return X\n",
"\n",
"def user_retention_dataset():\n",
" \"\"\" The observed data for model training.\n",
" \"\"\"\n",
" n = 10000\n",
" X_full = generator(n)\n",
" y = X_full[\"Did renew\"]\n",
" X = X_full.drop([\"Did renew\", \"Product need\", \"Bugs faced\"], axis=1)\n",
" return X, y\n",
"\n",
"def fit_xgboost(X, y):\n",
" \"\"\" Train an XGBoost model with early stopping.\n",
" \"\"\"\n",
" X_train,X_test,y_train,y_test = sklearn.model_selection.train_test_split(X, y)\n",
" dtrain = xgboost.DMatrix(X_train, label=y_train)\n",
" dtest = xgboost.DMatrix(X_test, label=y_test)\n",
" model = xgboost.train(\n",
" { \"eta\": 0.001, \"subsample\": 0.5, \"max_depth\": 2, \"objective\": \"reg:logistic\"}, dtrain, num_boost_round=200000,\n",
" evals=((dtest, \"test\"),), early_stopping_rounds=20, verbose_eval=False\n",
" )\n",
" return model"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "pp57A6WoqpzT",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 392
},
"outputId": "6f06d429-4eda-4dcc-b8d1-86af2fdb1628"
},
"source": [
"X, y = user_retention_dataset()\n",
"\n",
"# 値の確認\n",
"display(pd.DataFrame(X).head())\n",
"display(pd.DataFrame(y).head())"
],
"execution_count": 3,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Sales calls</th>\n",
" <th>Interactions</th>\n",
" <th>Economy</th>\n",
" <th>Last upgrade</th>\n",
" <th>Discount</th>\n",
" <th>Monthly usage</th>\n",
" <th>Ad spend</th>\n",
" <th>Bugs reported</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>0.719054</td>\n",
" <td>17.036984</td>\n",
" <td>0.283774</td>\n",
" <td>0.825265</td>\n",
" <td>0.803090</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>0.188017</td>\n",
" <td>13.464172</td>\n",
" <td>0.059483</td>\n",
" <td>0.287509</td>\n",
" <td>0.275391</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>0.387437</td>\n",
" <td>1.631930</td>\n",
" <td>0.167273</td>\n",
" <td>0.433489</td>\n",
" <td>1.396768</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>0.866165</td>\n",
" <td>7.710981</td>\n",
" <td>0.330207</td>\n",
" <td>0.235349</td>\n",
" <td>0.218303</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>0.585444</td>\n",
" <td>6.391478</td>\n",
" <td>0.299390</td>\n",
" <td>0.824211</td>\n",
" <td>0.815360</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Sales calls Interactions Economy ... Monthly usage Ad spend Bugs reported\n",
"0 2.0 2.0 0.719054 ... 0.825265 0.803090 1.0\n",
"1 3.0 3.0 0.188017 ... 0.287509 0.275391 0.0\n",
"2 2.0 2.0 0.387437 ... 0.433489 1.396768 1.0\n",
"3 2.0 2.0 0.866165 ... 0.235349 0.218303 0.0\n",
"4 2.0 2.0 0.585444 ... 0.824211 0.815360 1.0\n",
"\n",
"[5 rows x 8 columns]"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Did renew</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Did renew\n",
"0 0\n",
"1 1\n",
"2 0\n",
"3 0\n",
"4 0"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "v6picObB2h3b"
},
"source": [
"# train XGB \n",
"model = fit_xgboost(X, y)"
],
"execution_count": 4,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "XNEZEJq0qsJM",
"outputId": "6e8725bd-5329-40f0-c9f5-04ba47e4cbc9"
},
"source": [
"import shap\n",
"\n",
"explainer = shap.Explainer(model)\n",
"shap_values = explainer(X)\n",
"\n",
"clust = shap.utils.hclust(X, y, linkage=\"complete\")"
],
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"text": [
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:53] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:55] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
"[10:53:56] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 768
},
"id": "GztQW9Lw28I1",
"outputId": "29822360-3099-4427-fb14-b793ce980276"
},
"source": [
"shap.plots.bar(shap_values, clustering=clust, clustering_cutoff=1)\n",
"shap_values_df = pd.DataFrame(shap_values.values, columns=X.columns)\n",
"shap_values_df"
],
"execution_count": 6,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "execute_result",
"data": {
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" <th></th>\n",
" <th>Sales calls</th>\n",
" <th>Interactions</th>\n",
" <th>Economy</th>\n",
" <th>Last upgrade</th>\n",
" <th>Discount</th>\n",
" <th>Monthly usage</th>\n",
" <th>Ad spend</th>\n",
" <th>Bugs reported</th>\n",
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" <tr>\n",
" <th>0</th>\n",
" <td>-0.003374</td>\n",
" <td>0.039693</td>\n",
" <td>0.122691</td>\n",
" <td>-0.145341</td>\n",
" <td>-0.195122</td>\n",
" <td>0.061005</td>\n",
" <td>0.216014</td>\n",
" <td>0.125054</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>0.003976</td>\n",
" <td>0.061407</td>\n",
" <td>-0.143533</td>\n",
" <td>-0.111669</td>\n",
" <td>1.762967</td>\n",
" <td>-0.008006</td>\n",
" <td>-0.148988</td>\n",
" <td>-0.094597</td>\n",
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" <td>-0.002773</td>\n",
" <td>0.042184</td>\n",
" <td>-0.167981</td>\n",
" <td>0.174967</td>\n",
" <td>0.178945</td>\n",
" <td>-0.003724</td>\n",
" <td>0.234783</td>\n",
" <td>0.113212</td>\n",
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" <td>-0.000014</td>\n",
" <td>0.044768</td>\n",
" <td>0.231014</td>\n",
" <td>-0.135630</td>\n",
" <td>-0.495350</td>\n",
" <td>-0.036979</td>\n",
" <td>-0.249951</td>\n",
" <td>-0.168995</td>\n",
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" <td>0.023278</td>\n",
" <td>0.039174</td>\n",
" <td>-0.276473</td>\n",
" <td>0.054637</td>\n",
" <td>0.237839</td>\n",
" <td>0.132893</td>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" <td>0.068550</td>\n",
" <td>0.088124</td>\n",
" <td>-0.123355</td>\n",
" <td>-0.888675</td>\n",
" <td>-0.006573</td>\n",
" <td>-0.158371</td>\n",
" <td>-0.172496</td>\n",
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" <td>0.041895</td>\n",
" <td>0.016471</td>\n",
" <td>0.091934</td>\n",
" <td>-0.402528</td>\n",
" <td>-0.000107</td>\n",
" <td>0.237114</td>\n",
" <td>-0.214622</td>\n",
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" <tr>\n",
" <th>9997</th>\n",
" <td>0.007373</td>\n",
" <td>0.061914</td>\n",
" <td>-0.160303</td>\n",
" <td>-0.130761</td>\n",
" <td>-0.838286</td>\n",
" <td>-0.017909</td>\n",
" <td>-0.214989</td>\n",
" <td>-0.171793</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9998</th>\n",
" <td>-0.023900</td>\n",
" <td>-0.196993</td>\n",
" <td>0.193784</td>\n",
" <td>-0.105615</td>\n",
" <td>-0.138502</td>\n",
" <td>-0.044239</td>\n",
" <td>-0.243612</td>\n",
" <td>-0.175694</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9999</th>\n",
" <td>0.002089</td>\n",
" <td>0.055867</td>\n",
" <td>0.041769</td>\n",
" <td>-0.185834</td>\n",
" <td>1.628035</td>\n",
" <td>0.019911</td>\n",
" <td>0.088315</td>\n",
" <td>0.045542</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10000 rows × 8 columns</p>\n",
"</div>"
],
"text/plain": [
" Sales calls Interactions ... Ad spend Bugs reported\n",
"0 -0.003374 0.039693 ... 0.216014 0.125054\n",
"1 0.003976 0.061407 ... -0.148988 -0.094597\n",
"2 -0.002773 0.042184 ... 0.234783 0.113212\n",
"3 -0.000014 0.044768 ... -0.249951 -0.168995\n",
"4 -0.003147 0.036879 ... 0.237839 0.132893\n",
"... ... ... ... ... ...\n",
"9995 0.002496 0.068550 ... -0.158371 -0.172496\n",
"9996 -0.001591 0.041895 ... 0.237114 -0.214622\n",
"9997 0.007373 0.061914 ... -0.214989 -0.171793\n",
"9998 -0.023900 -0.196993 ... -0.243612 -0.175694\n",
"9999 0.002089 0.055867 ... 0.088315 0.045542\n",
"\n",
"[10000 rows x 8 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 6
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "u9x1VkDb27T7",
"outputId": "86295bfe-acf1-4bc8-cb5e-20d6e40c0f47"
},
"source": [
"max = len(X.columns)\n",
"\n",
"for i, col in enumerate(X.columns):\n",
"\n",
" df = pd.merge(X[[col]], shap_values_df[[col]], left_index=True, right_index=True)\n",
"\n",
" plt.figure()\n",
"\n",
" ax1 = plt.subplot(1, 1, 1)\n",
" ax2 = ax1.twinx() # 二つ目の軸を定義\n",
"\n",
" ax1.scatter(df[col + '_x'], df[ col + '_y'])\n",
" X[col].hist(ax=ax2, alpha = 0.3)\n",
"\n",
" ax1.set_ylabel('Shap value')\n",
" ax2.set_ylabel('Data count')\n",
"\n",
" ax1.set_xlabel(col)\n",
" "
],
"execution_count": 7,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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v+s/rjOPmNTeY1vr/gL8Fng/8Aij2vT4OfLHam1ST4J4VEbdpfN+uKxqbWV1q+dKuRR/wnhPmP5OkjptwwsTtDlDtgJM+kq7fRYfv15rAmiwiLgMuk/S+iPhCvfep5hncHyS9AAgASW8DNtf7hmbW25rxLCvXNyG5dYlyXae5MuNIdgLLb72f67ugWHWpiPiCpFdJ+nNJS4o/1V5fTQvuvSSV+l8saROwDq/LZmZ1GBzawtW3bZj2fUT6G3dRF4+On9h1Oji0peyoz9GxnXzuhjWc0sLBMM0m6WvAC4A7geIigQEsr+b6KRNcuiDpIkkFoC8inqgzVjPrQY2eErDnjD62TyhaORbJ4JVua8GVs+CQ2Sy7eV3ZY7/rvtW8jwYOjzprSk6Z4CR9fMI2ABFxcT1vaGa9o9ErWS88bE7FBVGznnbQSpWeYz5/1swMommqXwPPo87HYtU8gxsp+RkD3gjMq+fNzKx3fH3lepbdvK5hya2PZKRgpblhvbTmWqValhe84bCMImqaOcA9km6QtKL4U+3F1XRRXlq6LekfSZa4MTMr6+sr11dsadWrmCbLjSxs9UTsrE2sdlKc+tBNz99SF03n4npKdT2LZPVtM7OyGp3cYHzlEdj9y70Xnr+Vasd5e40WEf85neureQZ3F8+MUcoBzwX8/M3MWmpi5ZFu/3I3kPQEz+SfPLAHMBIR+1RzfTUtuDeXvN4BPJSuxm1mtptLf/Sbht+zkM85ofWgiHh28bWSEY4nAwuqvb7iIJNi7S/giZKfbcA+6X4zs3EGh7Y0ZfHSxcce1PB7WmeJxPXAG6q9ZrIW3C9Imobl1l8I4JDawjOzbteISdzluPXWmySdWrLZRzIv7qlqr6+Y4CJi/jTiqoqkE4HLSJ7tLYuISyYc/2Pgn4EjgdMj4tpmx2RmtStWKBkZHZv65Br10vD/didpFrAMeBlJQ+c9wBrgmyTTx9YDp0XEI2mX4mXAm4CtwFkR8csa3/ItJa93pPc/udqLqxpFKWlf4FBgr+K+iPhZtW9S4Z454EvA64GNwO2SVkTEPSWnbQDOAv5uOu9lZs0zOLSlYmWN6eq14f/VKq0O0+JRpJcBP4yIt0nKk4yq/5/ATRFxiaQLgQuBD5PMmT40/TkO+DI1lryOiHdPJ9hq1oM7B/gZydy3T6b/vWg6b5o6FlgbEUMRMQpcw4TMHBHrI2I1TLnYrpll5GuD9zflvn2Q2Tps7WzigrHDI6Msv/V+Boe2NPV9JT0H+GPgcoCIGI2IR0m+t69KT7sKOCV9fTKwPH12NgjMkrR/je95gKTvSno4/fmOpKqnqVXTgjsfOAYYjIjXSHox8L9qCbKCucADJdsbqXNBC0nnAucCzJ07l4GBgbqD2vaUB4ia1eK8lzS+RJaA2Xvvyd4zfse2Db9r+P072ewntvG+w3f/nX/GE79lYODh6dx6hqRVJdtLI2JpyfZ84PfAlZJeTjJO43xgv4goltJ6ECiu2VPuO34utZXduhL4d+Dt6fYZ6b7XV3NxNQnuqYh4ShKS9oyI30hqq3ow6V/CUoBCoRALFy6s+1433vNQg6Iy6zyX/ug340ZBvuR5e/PBP31xxfMHh7aw7K7Gd08W8jkuO/2oht+3G3xmYBWVOt/WL144nVvviIijJzk+A3gl8L6IWCnpMpLuyF0iIiQ1cm2H50bElSXbX5X0t9VeXE2C25g+WLwe+LGkR4BG9ElsAg4s2T4g3WdmGZiY3ADuffBJzlm+iv2fsycPPbZ917OCfE6MjjVvjZpmDFbpFpUKLbdgMM5GYGNErEy3ryVJcA9J2j8iNqddkMVmZCO+47dIOgO4Ot1eDFTdFzvlM7iI+LOIeDQiLgL+nqT/9ZTJr6rK7cChkuanDytPB6ouomlmjTXZ/LXNJckNaGpyA4+cnEylQsvNHowTEQ8CD5T04L0OuIfke/vMdN+ZwPfS1yuAJUosAB4r6cqs1nuA00i6PjcDbwOqHnhSTamufwGuiYhbplsXrFRE7JB0HsmglRxwRUTcLeliYFVErJB0DPBdYF/gLZI+GREvbVQMZpZo9gCFWuT6mrPqd7fIuBbn+4BvpI2SIZJk0wd8S9LZJL17p6Xn/oBkisBakmkCNY+IjIj7gZPqDVZTrSMn6UzgHcBhJMnmmohYNelFGSoUCjEyMlL39X4GZ73oL5avaotFsQv5HIuPPcgjJ+u06PD9pj6pAklbI6LQwHCmTdJVwPnpaM3ilLVLI+I91VxfzXI5VwFXpeW53gp8RtJBEXHoNOI2szbxd9++sy2S27Ilk41vsB51ZDG5AaQTyKsefVTNgqdFLwReDBwMNL6aqpm13KU/+g2Pbst+aoyfuVkFfWmrDUhqJFPDMm/VPIP7LPBnwG9JJmN/qjSjmlln+vvv3cXmx7ZnHQZ98jM3q+hS4FZJ30633w78Q7UXV5MJfwscHxGNX8HQzDJx6Y9+0xbJbUafOOtV8/zMzcqKiOXp5PPXprtOnVDOcVLVPIP713qDM7NsTKxVuN+z801ZxqZeHkxi1UoTWtVJrVTVfZlm1noTq/Tnc2KPXB8jo2P0F/IcecA+rN74eNmJv0XDI6OTHm8lJzZrJSc4szY1OLSFK3++jtI51aNjwehYkuyGR0YZWNM5Tw7OOWG+E5u1VLXL5bwSOIFk/Z+f17Gmj5lNYWK34vanx2hywZCWcnKzVqtmuZyPkyyBMBuYQ1JJ+mPNDsysl5RbAqWb6jEq6wCsI0laIOl2SU9KGpU0Junxaq+vpgX3TuDlEfFU+oaXAHcCn64vZDMrba0V8rmuSmbl/Mlhc7IOwTrTF0nqFH8bOBpYAryo2ourSXC/I1nJ+6l0e09c9d962MSBH6UDJ6pZaXnis7VuT24LD5vDGcfNyzoM61ARsVZSLiLGSHoQ7wA+Us211SS4x4C7Jf2Y5Bnc64Hb0iLMRMTf1Bm3WccZHNrClbesY6yktP7I6BhX/nwda3//BLesHWY0PTg8Msqym9dx9W0bxo0cvPq2DV31bG0yHlhi07Q1Lex8Z1p0ZDM1VOCqJsF9N/0pGqgpPLMuct0dm8Ylt6KxoOKIxmIChGSgRbe32Eo5udk0vYskoZ0HvJ9kfblTq7242mLLZj1vcGhL3fPJxgKW3byOZTc3fvXrduX6ktYAp0TEZSSPyD4JIOl84LJqLq5mFOWhkq6VdI+koeLPtEI26zCDQ1t6KjlNVysW4LSecGaZfWdVe3E1XZRXAp8APg+8hmcWuDPrGctvXZ91CB2jxQtwWheStBj4c2C+pBUlh54NDFd7n2oS3MyIuEmS0tVVL5L0C+DjNUVs1sFGe2VUyAT5XN+uQTNFfcDEx5BOatZgt5AMKJlDsqJA0RPA6mpvUk2C2y6pD7hP0nkkUwT2riFQM+tAxaQ11bQHs0ZLG1P3A8dP5z7VJLjzgWcBfwN8imTZgnL9omZdaXBoS9YhtFzxGdqCQ2Y7oVlmJC0AvgC8BMgDOWAkIvap5vopn6VFxO0R8WREbIyId0fEqRExOK2oU5JOlLRG0lpJF5Y5vqekb6bHV0qa14j3NavF1wbvzzqEluov5Fly/MFObNYOvggsBu4DZgLnAF+q9uJqVvR+EXABcHDp+RHx2ooXVUFSjiTQ1wMbgdslrZiwmN3ZwCMR8UJJpwOfAd4xnfc1q9X2HWUmvnWpQj7HZ996ZNZhmO3S7Eom3wa+Avwb0MgZqscCayNiCEDSNcDJjF/Y7mTgovT1tcAX08EuvfnE36yJcoLFxx6UdRhmpZpeyWRHRHy53ugmMRd4oGR7I3BcpXMiYoekx0hWNRhXMkLSucC5APm8J5eaVas4ItIDSKxNlatk8tZqL66Y4CT1py//j6S/JinXtb14PCKqnovQbBGxFFgKUCgU3Lozm4SLH1uniIj7JT03ff3JWq+frAX3C5LiysWlnC4ofV/gkFrfbIJNJNm46AB2X6WgeM5GSTOA5wC9N6TNrEaFfI5j5u/LLWu37JrDJ5Jla5zcrN1JEkmBkfNIWnCStAP4QkRcXO19Kia4iJg/7SgndztwqKT5JInsdJKZ66VWkExJuBV4G/ATP3+zVikufdMO8jmx5Ph5u7oQS5flmayb0cnMOtT7gVcDx0TEOgBJhwBflvT+iPh8NTdRpXwh6RjggYh4MN1eQtL3eT9wUSO6KCW9CfhnkrkNV0TEP0i6GFgVESsk7QV8DTiKpDzL6cVBKZUUCoUYGRmpO6Yb73mo7mutO0xc7y1LhXyOy04/KuswrEMsOny/uq+VtDUiCg0Mp27pSMnXR8TE8RbPBX4UEVX9TzFZF+W/AovSm/4xcAnwPuAVJM+73lZH3ONExA+AH0zY9/GS108Bb5/u+5hVa3BoC8tvvX+38lRZEB7VaD1rj4nJDSAifi9pj2pvMlmCy5W00t4BLI2I7wDfkXRnbbGadYbr7tjUFsltYpekWY+ZbF2qqtesmjTBSZoRETuA15EOw6/iOrOOVet6b+ecMH/Xs7CJ8rk+lhx/MD9f+3vuffDJivfICd79aq98bVbi5ZIeL7NfwF7V3mSyRHU18J+S/gBsA/4LQNILgcdqCNSsY/QX8jUludJajaUDP0oHfExMXJXOM+sEaRWqVcCmiHhzOlDwGpI5yr8A3hURo5L2BJYDf0Qy+v0dEbG+mveIiFwjYp1sFOU/SLoJ2J/koV5xNEofybM4s65z6lFzq17YVBO2qy1M7ALG1uHOB+4FigWPPwN8PiKukfQVkhKLX6YNSi1OWvIkIgYj4rsRMVKy778j4pfND82s9WpJPJ6vYr1G0gHA/wCWpdsiWWHm2vSUq4BT0tcnp9ukx1+Xnt8yXfcsrb+/n4GBgbqv3/bUjsYFYx3nye07+OAR1f0bELBtw13NDcisBgMP3zudy2dIWlWyvTStElXqn4EPkaysDUm35KPpWA1ISi7OTV9XVWqxmbouwQ0PD7Nw4cK6r/c8uN52/tdWsTOq/99i2ZIjmhiNWW0WTmMeHEnd4aMrHZT0ZuDhiPiFpIXTeaNW6boEZzYdO2vod+wvuLC39ZRXAyelBTr2InkGdxkwq2TEfWnJxcxLLVa97ICZjXfqUXOnPsmsS0TERyLigIiYR1Ja8ScR8U7gpzxT+ONM4Hvp62KpRcio1KITnFmdPBLSDIAPAx+QtJbkGdvl6f7Lgdnp/g8AF7Y6MHdRmtWhpUPBzNpMRAwAA+nrIZIFrCeek3mpRSc4M2pfOcBTBMzanxOc9bx6Cix7gIlZ+/MzOOt5tRZYzuf6PMDErAO4BWc9r5bak64dadY5nOCs5xXyuaoWNy3kc3z2rUe2ICIzawQnOOtZxYEl1a7c7cVHzTqLE5z1pHoGlrhb0qyzOMFZzxkc2sIVN68j+3W7zayZMhlFKalf0o8l3Zf+d98K5/1Q0qOS/qPVMVp3KrbcnNzMul9W0wQuBG6KiEOBm6hcwuVzwLtaFpV1vVqnBJhZ58qqi/JkYGH6+iqSki8fnnhSRNzUKcsyZKk4WGJ4ZLTnhrHX+tlrmRJgZp0tqwS3X0RsTl8/CExrESNJ5wLnAuTzvVVhYuJgieGRUZbfej/QfYMiSpNZH+zWzTg8Msqym9ex7OZ1FZNdPidGx1xoy6wXNC3BSboReF6ZQx8t3YiIkDStb5x01dmlAIVCoae+vcp1uY2O7eTq2zZ0VYKbmMin6mQcHhnlyp+v27V99W0bqp4OYGbdoWkJLiIWVTom6SFJ+0fEZkn7Aw83K45uV6nLbWR0jMGhLRWTXDVde43u+qzlfhPP3f70WM3PzsYClt+6nrGdgRttZr0nqy7K4kJ4lzB+gTybYKqk0F/IV0xyxer4xesL+RzAbi2Zct2a0+36nBj3kQfswy1rh6u6X7n3rpe7I816l1q8wGryptJs4FvAQcD9wGkRMSzpaOAvI+Kc9Lz/Al4M7E2y1PnZEXHDZPcuFAoxMjJSd2w33vNQ3dc2WrnJyDnBXnskpaWKiWNgzR8q3iOf66u65dNfyPPZtx456TyxYpKdmHRhfCJ96umxqlpNxfcs9aHvrG67wSALD5vDGcfNyzoMs0ktOrz+4QyStkZEoYHhZC6TBNdMnZzgSls91dZHzPVBTuUHTmRg6lgAAA7qSURBVJQbiDGVhYfNmTRhwu5JMydAUO/o+2VLjh63fc7yVfXdqIkmxmjWjpzgxnMlkwxNTGilrZ5qB0SM7YQZM5SODnwmw9TScis1VXLrg93uOxZMawXQc5avIid496vns+CQ2VUn91Z5yfP2zjoEM6uD14PLSLH7sdgVNzJaXZdeOdt37GR0bOeuv8z+Qp4lxx/clEU5mzVFeixg2c3reO+//7KtkhvAQ0+0V3epmVXHCS4jzaioUbzbkQfsw4JDZnPkAfs09P6tsH1H+1UZabfngWZWHXdRZqSZX5oDa/4wZVejVa8ZLWEzaz634DLiL83OURwlamadxQkuI53YfdiLFh42p6sqwpj1EndRZmBwaAu3rB3OOgybRCGfY/GxBzm5mXUwJ7gWmapQsLWPPWf0cdnpR2UdhplNkxNcCwwObeHKn6/bNQ3Aya29vWvBwVmHYGYN4GdwLXD1bRtc7NfMrMWc4Fqg3SYu2+SKRarNrLO5i7IGE0trAbuKHk+23Ix1Fk/sNusOTnBVmljZv7RVVs1yM9Y5PEfRrDu4izJ1/R2bePUlP+Gc5av40HdWMzi0ZdzxqUprFVfRrvZ8a0/5XJ8ndpuVIelAST+VdI+kuyWdn+7vl/RjSfel/9033S9J/yJpraTVkl7Z6pid4EiS2wXX/opNj24DkhbZlbesG5fkqum2Kq6iXe351l6KRao9982srB3AByPicGAB8F5JhwMXAjdFxKHATek2wBuBQ9Ofc4Evtzpgd1ECn/w/d/P0hGGOYzvh8pvXsezmdTX9FuBnbp2pD3ZbeNXMnhERm4HN6esnJN0LzAVOBhamp10FDAAfTvcvj2TR0UFJsyTtn96nJbouwfX39zMwMFDTNe95wbYGRrCDvsfX8sEjPC+g02zbcFfWIZhNy8DD907n8hmSSlcbXhoRS8udKGkecBSwEtivJGk9CBRXXZ0LPFBy2cZ0nxNcvYaHh1m4cGFN15x14fcb9v7ttlinVae/kOezRx2RdRhm07JwGit6AzsiYsql6yXtDXwH+NuIeFzSrmMREZLa5rd7P4MDZs3co2H3cnLrTB5YYjY1SXuQJLdvRMR16e6HJO2fHt8feDjdvwk4sOTyA9J9LZNJgqs06mbCOa+QdGs6Wme1pHc0K56LTnope/Rp6hOtKxXyOQ8sMZuCkqba5cC9EfFPJYdWAGemr88Evleyf0k6mnIB8Fgrn79Bdi24SqNuSm0FlkTES4ETgX+WNKsZwZxy1Fw+9/aXN+PW1ubyuT4WH3tQ1mGYdYJXA+8CXivpzvTnTcAlwOsl3QcsSrcBfgAMAWuBfwP+utUBZ/UMrtKom10i4r9LXv9O0sPAc4FHmxHQqvu9fE23y+f6eNUL+1m98XGGR0YrVqAxs91FxM1Apa6u15U5P4D3NjWoKWSV4CqNuilL0rFAHvhthePnksyzIJ+vvQrFx66/i68Pbpj6ROtY49Z3Oy7raMysFZqW4CTdCDyvzKGPlm5MNeomfWj5NeDMiChbGiQdyroUoFAo1DyC5xsrndy6lVtpZr2raQkuIhZVOibpoeKEvwmjbiaetw/wfeCjETHYpFCJthnUWp18rq8hZcAK+RzHzN+XgTV/qHhOfyFfc1WWWhZ0LeRzPPX0WFXLCQmI9Bp4ptD1kQfswy1rh8f9meRzfa5KYtbjsuqiLI66uYTxo252kZQHvksyE/7a1obXvootkuKqBvXoA95zwvxdX/63r3uk7PSG4ntNLBqdU5Jodk5ISjnBu189f1zB6WpWXyg9r96E9cLnPnvcPdxqMzNFBs0XSbOBbwEHAfcDp0XEsKSjgb+MiHMknQFcCdxdculZEXHnZPcuFAoxMjJSUzzzGjjRe7oEnH3CfIDdEku5L/nBoS1cfduGmuffLVvyzHzOcisflL7XxARUnDNW+r7jnnE1QLn3dMIym9yiaUz0lrQ1IgoNDCdzmSS4Zur0BHfOCeVbQNV+yZdeU6mrsL+Q363uohOKWedzghuv60p1dbL+Qn5cUllwyOyak0zpNZVaZuWqdtTzXmZm7cwJrk00Yx2yYsJyy8zMepETXBtoZuJxy8zMepUTXEYaPSjDzMzGc4LLQCGf47LTj8o6DDOzrublclos14eL+5qZtYBbcC2Uz4klx89zt6SZWQs4wbXQ/37nH2UdgplZz3AXZYt4OVUzs9ZygmuR7qoXY2bW/pzgWqS/UPs6dWZmVj8nuBZpdJUSMzObnBNci3jkpJlZaznBtcAM/ymbmbWcv3pbYM8ZuaxDMDPrOU5wU9j/OXtO+x61LkZqZmbT5wQHzJq5R8Vj23dMf4C/R1CambWeExxw0UkvrXhseGR00msXHjaHQr5yF2Qz1nkzM7OpKaK7piAXCoUYGRmp+bqjLv4Rj2x9erf9xdZXuURXblWAwaEtXmDUzDKx6PD96r5W0taIKDQwnMxlUotSUj/wTWAesB44LSIemXDOwcB3SVqZewBfiIivNCumT7zlpXzkurvY9vQzz8tKW1/Lb72f0bGd446VWxXAC4yambWHrIotXwjcFBGXSLow3f7whHM2A8dHxHZJewO/lrQiIn7XjIBOSRPZxf9xT8XWl1tmZmadI5MuSklrgIURsVnS/sBARBw2yfmzgTuABVMluHq7KItuvOehuq81M8uSuyjHy2qQyX4RsTl9/SBQ9m9F0oGSVgMPAJ+plNwknStplaRVO3bsaE7EZmbWUZrWRSnpRuB5ZQ59tHQjIkJS2WZkRDwAHCnp+cD1kq6NiN2aWBGxFFgKSQtu2sGbmVnHa1qCi4hFlY5JekjS/iVdlA9Pca/fSfo18P8C1zY4VDMzq4KkE4HLgBywLCIuyTikSWXVRbkCODN9fSbwvYknSDpA0sz09b7ACcCalkVoZma7SMoBXwLeCBwOLJZ0eLZRTS6rBHcJ8HpJ9wGL0m0kHS1pWXrOS4CVkn4F/CfwjxFxVybRmpnZscDaiBiKiFHgGuDkjGOaVNdN9Ja0E9g2jVvMAHpppEqvfV7wZ+4V/sy1mQn8smR7aTq+AQBJbwNOjIhz0u13AcdFxHn1BttsWc2Da5qImFarVNKqiDi6UfG0u177vODP3Cv8mc21KM3MrBqbgANLtg9I97UtJzgzM6vG7cChkuZLygOnkwwYbFtd10XZAEunPqWr9NrnBX/mXuHP3EARsUPSecANJNMEroiIu5v1fo3QdYNMzMzMwF2UZmbWpZzgzMysK/VkgpN0oqQ1ktamy/VMPL6npG+mx1dKmtf6KBuris/8AUn3SFot6aZ0Pb6ONtVnLjnvrZJCUscPr67mM0s6Lf27vlvSv7c6xkar4t/2QZJ+KumO9N/3m7KIs1EkXSHp4bR8YbnjkvQv6Z/HakmvbHWMbSMieuqH5OHob4FDgDzwK+DwCef8NfCV9PXpwDezjrsFn/k1wLPS13/VC585Pe/ZwM+AQeDorONuwd/zoSRLT+2bbv8/Wcfdgs+8FPir9PXhwPqs457mZ/5j4JXAryscfxPwfwEBC4CVWcec1U8vtuCqKTdzMnBV+vpa4HWS1MIYG23KzxwRP42IrenmIMkcl05WbVmhTwGfAZ5qZXBNUs1n/gvgSxHxCEBETFrovANU85kD2Cd9/RygKYsmt0pE/AwYnuSUk4HlkRgEZqVF7XtOLya4uSTryxVtTPeVPScidgCPAZ28fHc1n7nU2SS/AXayKT9z2nVzYER8v5WBNVE1f88vAl4k6eeSBtPq8J2sms98EXCGpI3AD4D3tSa0zNT6/3vX8jw4G0fSGcDRwJ9kHUszSeoD/gk4K+NQWm0GSTflQpJW+s8kHRERj2YaVXMtBr4aEZdKOh74mqSXRcTOrAOz5urFFlw15WZ2nSNpBkm3xpaWRNccVZXYkbSIZEHakyJie4tia5apPvOzgZcBA5LWkzyrWNHhA02q+XveCKyIiKcjYh3w3yQJr1NV85nPBr4FEBG3AnsBc1oSXTY6rqRWs/Rigqum3EzpenVvA34S6dPbDjXlZ5Z0FPCvJMmt05/LwBSfOSIei4g5ETEvIuaRPHc8KSJWZRNuQ1Tzb/t6ktYbkuaQdFkOtTLIBqvmM28AXgcg6SUkCe73LY2ytVYAS9LRlAuAxyJic9ZBZaHnuiijQrkZSRcDqyJiBXA5STfGWpKHuadnF/H0VfmZPwfsDXw7HU+zISJOyizoaaryM3eVKj/zDcCfSroHGAMuiIiO7Z2o8jN/EPg3Se8nGXByVif/wirpapJfUuakzxU/AewBEBFfIXnO+CZgLbAVeHc2kWbPpbrMzKwr9WIXpZmZ9QAnODMz60pOcGZm1pWc4MzMrCs5wZmZWVfquWkCZtWQNAbcVbLrmoi4JKt4zKx2niZgVoakJyNi76zjMLP6uYvSrAaSjpF0i6RfSbpN0rMl7SXpSkl3pWuOvSY99yxJ10n6oaT7JH225D6L0/N/LekzJfuflPS5dK22GyUdK2lA0pCkk9JzfibpFSXX3Czp5a38czDrBE5wZuXNlHRnyc870lJQ3wTOj4iXA4uAbcB7gYiII0gK+14laa/0Pq8A3gEcAbxD0oGSnk+yRM9r0+PHSDolPb9AUhrupcATwKeB1wN/BlycnnM5aZFoSS8C9oqIXzXtT8KsQ/kZnFl52yLiFaU7JB0BbI6I2wEi4vF0/wnAF9J9v5F0P0mNR4CbIuKx9Lx7gINJll4aiIjfp/u/QbKI5fXAKPDD9Nq7gO0R8bSku4B56f5vA38v6QLgPcBXG/vRzbqDE5xZc5WuyjDG1P/PPV1SJ3Fn8fqI2JmubEFEbJX0Y5KFLU8D/qixIZt1B3dRmlVvDbC/pGMA0udvM4D/At6Z7nsRcFB6biW3AX8iaY6kHEm35n/WGMsy4F+A24urc5vZeG7BmZU3U9KdJds/jIgLJb0D+IKkmSTP3xYB/xv4ctqNuIOkWv32dFWG3UTEZkkXAj8FBHw/Ir5XS3AR8QtJjwNX1vzJzHqEpwmYdaB0oMoA8GKvTG1WnrsozTqMpCXASuCjTm5mlbkFZ2ZmXcktODMz60pOcGZm1pWc4MzMrCs5wZmZWVdygjMzs670/wMNXkbw1cp/YQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "1J-JlCXcrVoe"
},
"source": [
""
],
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 463
},
"id": "cwOuzv5wrdhP",
"outputId": "5cad3084-993f-4422-a72f-bb2f6b03c837"
},
"source": [
"import graphviz\n",
"names = [\n",
" \"Bugs reported\", \"Monthly usage\", \"Sales calls\", \"Economy\",\n",
" \"Discount\", \"Last upgrade\", \"Ad spend\", \"Interactions\"\n",
"]\n",
"g = graphviz.Digraph()\n",
"for name in names:\n",
" g.node(name, fontsize=\"10\")\n",
"g.node(\"Product need\", style=\"dashed\", fontsize=\"10\")\n",
"g.node(\"Bugs faced\", style=\"dashed\", fontsize=\"10\")\n",
"g.node(\"Did renew\", style=\"filled\", fontsize=\"10\")\n",
"\n",
"g.edge(\"Product need\", \"Did renew\")\n",
"g.edge(\"Product need\", \"Discount\")\n",
"g.edge(\"Product need\", \"Bugs reported\")\n",
"g.edge(\"Product need\", \"Monthly usage\")\n",
"g.edge(\"Discount\", \"Did renew\")\n",
"g.edge(\"Monthly usage\", \"Bugs faced\")\n",
"g.edge(\"Monthly usage\", \"Did renew\")\n",
"g.edge(\"Monthly usage\", \"Ad spend\")\n",
"g.edge(\"Economy\", \"Did renew\")\n",
"g.edge(\"Sales calls\", \"Did renew\")\n",
"g.edge(\"Sales calls\", \"Product need\")\n",
"g.edge(\"Sales calls\", \"Interactions\")\n",
"g.edge(\"Interactions\", \"Did renew\")\n",
"g.edge(\"Bugs faced\", \"Did renew\")\n",
"g.edge(\"Bugs faced\", \"Bugs reported\")\n",
"g.edge(\"Last upgrade\", \"Did renew\")\n",
"g.edge(\"Last upgrade\", \"Ad spend\")\n",
"g"
],
"execution_count": 8,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<graphviz.dot.Digraph at 0x7fbe095a8610>"
],
"image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n -->\n<!-- Title: %3 Pages: 1 -->\n<svg width=\"570pt\" height=\"332pt\"\n viewBox=\"0.00 0.00 569.82 332.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 328)\">\n<title>%3</title>\n<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-328 565.8241,-328 565.8241,4 -4,4\"/>\n<!-- Bugs reported -->\n<g id=\"node1\" class=\"node\">\n<title>Bugs reported</title>\n<ellipse fill=\"none\" stroke=\"#000000\" cx=\"43.5611\" cy=\"-18\" rx=\"43.6222\" ry=\"18\"/>\n<text text-anchor=\"middle\" x=\"43.5611\" y=\"-15.5\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#000000\">Bugs reported</text>\n</g>\n<!-- Monthly usage -->\n<g id=\"node2\" class=\"node\">\n<title>Monthly usage</title>\n<ellipse fill=\"none\" stroke=\"#000000\" cx=\"139.5611\" cy=\"-162\" rx=\"45.8316\" ry=\"18\"/>\n<text text-anchor=\"middle\" x=\"139.5611\" y=\"-159.5\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#000000\">Monthly usage</text>\n</g>\n<!-- Ad spend -->\n<g id=\"node7\" class=\"node\">\n<title>Ad spend</title>\n<ellipse fill=\"none\" stroke=\"#000000\" cx=\"199.5611\" cy=\"-90\" rx=\"32.2534\" ry=\"18\"/>\n<text text-anchor=\"middle\" x=\"199.5611\" y=\"-87.5\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#000000\">Ad spend</text>\n</g>\n<!-- Monthly usage&#45;&gt;Ad spend -->\n<g id=\"edge8\" class=\"edge\">\n<title>Monthly usage&#45;&gt;Ad spend</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M154.0854,-144.5708C161.5637,-135.5968 170.8087,-124.5028 179.0061,-114.666\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"181.8705,-116.6958 185.5836,-106.7729 176.493,-112.2145 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},
"metadata": {
"tags": []
},
"execution_count": 8
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "GABqgO4-umvI"
},
"source": [
"def marginal_effects(generative_model, num_samples=100, columns=None, max_points=20, logit=True, seed=0):\n",
" \"\"\" Helper function to compute the true marginal causal effects.\n",
" \"\"\"\n",
" X = generative_model(num_samples)\n",
" if columns is None:\n",
" columns = X.columns\n",
" ys = [[] for _ in columns]\n",
" xs = [X[c].values for c in columns]\n",
" xs = np.sort(xs, axis=1)\n",
" xs = [xs[i] for i in range(len(xs))]\n",
" for i,c in enumerate(columns):\n",
" xs[i] = np.unique([np.nanpercentile(xs[i], v, interpolation='nearest') for v in np.linspace(0, 100, max_points)])\n",
" for x in xs[i]:\n",
" Xnew = generative_model(num_samples, fixed={c: x}, seed=seed)\n",
" val = Xnew[\"Did renew\"].mean()\n",
" if logit:\n",
" val = scipy.special.logit(val)\n",
" ys[i].append(val)\n",
" ys[i] = np.array(ys[i])\n",
" ys = [ys[i] - ys[i].mean() for i in range(len(ys))]\n",
" return list(zip(xs, ys))\n"
],
"execution_count": 9,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "5fNrz26O1vHg"
},
"source": [
""
],
"execution_count": 9,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "7j8vJlYY2Kua",
"outputId": "eef73d43-426e-4556-e3e3-a84e2d83374d"
},
"source": [
"max = len(X.columns)\n",
"\n",
"real_value = marginal_effects(generator, 10000, X.columns)\n",
"for i, col in enumerate(X.columns):\n",
"\n",
" df = pd.merge(X[[col]], shap_values_df[[col]], left_index=True, right_index=True)\n",
" real_x, real_y = real_value[i]\n",
"\n",
" plt.figure()\n",
"\n",
" ax1 = plt.subplot(1, 1, 1)\n",
" ax2 = ax1.twinx() # 二つ目の軸を定義\n",
"\n",
" ax1.scatter(df[col + '_x'], df[ col + '_y'])\n",
" ax1.plot(real_x, real_y)\n",
" X[col].hist(ax=ax2, alpha = 0.3)\n",
"\n",
" ax1.set_ylabel('Shap value')\n",
" ax2.set_ylabel('Data count')\n",
"\n",
" ax1.set_xlabel(col) "
],
"execution_count": 10,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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27DvID84ezvC+3eMSa0c7BcRSuu6BS1eW4IwxEVu5rZatew9wVukRCIFXTB59ZA/u+upxnDS4Ny9+UsW9r62iuq6Rg80tPPD6GjbX1HPLWcM55siecYnzv2enxsjNJIfdgzPGROytlTvIz/VwypDCkOfmd8nmO2cO5YTK3Tz18SbunPMZ/XrlsXFXnXO8uFdcYrz6bx/y/trq0CcmUDpXMklHluCMta0xEdld10jFphomHXckuZ7wJoEEYcLwIkb0687Md9ezYVcd35pQwtijQifIaMxftzvlkhvAL/+5zBJcAlmCM8ZE5O3VOwAoK+0b8bVH9OjKHeeXsqe+iaLuXWIdWpuXkrjXLZhM7CiQyizBGWPC1tTayrurdzF6UEHUCcqTlRXT5DZ/3W5eqqiiuq6RwvxcLhlTTHVd5BvNTeaxRSbGmLAt3FBN7cFmzjo68tFbPMxft5vHP9zYltCq6xqZ9d76JEcVXDIrqXQ2luCMMWF7c+VO+vXswrFxWvUYqac/3kRjSzL6AkTPOgokjiU4Y0xY1u+qY/2uOs4uPSLqYsqxNH/dbuoaU2N/WyRs20LiWIIzxoTlzZU76JKdxenD+yQ7FMAZvRkTjC0yMcaEVHuwmQUbqvnSiKKYNx+NRrqO3vzx1sncUtPAgII8pk4qta0EMZL8f6nGmJT33pqdNLcqZ5ceEfrkOJi/bjdPf7wpY5Kal7dOpreUWFVNA3e85HQ7sCTXcTZFaYwJqlWVt1btpLRfj6RUw3/yow3Mem99SiS3grwcNkz/codew+Nz+9JfncyGppaUXIgiIo+IyA4R+cznWKGIzBORNe7vvd3jIiIPiEiliCwRkZN8rrnWPX+NiFwbz5gtwRljgvr08xqq6xo555jEbw2Yv2435at2Jfx9/cnJEu666LgOv06LT9PTLQEWnAQ6nmR/B85vd2wa8IaqjgDecB8DXACMcH/dBDwITkIE7gROA04F7vQmxXiwBGeMCerNVTvo3S2H0QMLEv7eqbCQRIDigjxmXD66bdqwIC8nJq8daEScin3jVPUdoH39s4uBx9yvHwMm+xx/XB3zgQIR6Q9MAuaparWq7gHmcXjSjJmMuwdXWFhIeXl5ssNIKw0HmpMdgklRTS2tXFjUQO/BuTRuXpbw9/9u6cGEv2d7gwq7UZCXBXvXUF6+BoC7ThU+r47u/41A2/eoqaNbqNrTckgboSwRinu3JOP7WLaILPR5PFNVZ4a4pp+qbnW/3gb0c78uBj73OW+zeyzQ8bjIuARXXV1NWVlZssNIK1Zs2QQy++NNvL26md9ddgJ5XWMzaonEveULQ58UZ3k5LfzmkmMPW/Qx9I5XaNUAF4Ww4eqytq9TaBVls6qOjfZiVVURifJPJD4yLsEZY2LjQHML71fuYmxJb3omIbnNX7c74e/pT0NTC3fNWXZYEoo2ubU3eUzxIQltdkUVE6a/mQoJLxzbRaS/qm51pyB3uMergEE+5w10j1UBZe2Ol8crOEtwxqSpusZm3l69k6bmVrKzhKwswZMleMT9vd2v7KwsSoq6UZCXG9brf7h2NweaWzn76MRvDZi/bjcPp1BNyZqGJmoanE4A3qX8eTlZNDRFVyYsUF+4UNsGUmi05zUHuBaY7v7+ss/x74vIMzgLSva6SXAu8D8+C0vOA+6IV3CW4IxJQw1Nzdz3+ho27KqL+NrSfj04dUghJx/Vm+5d/H8LUJQ3V+6gpE83hhTldzTcsKXLfreGppYgfcxDmzF3ld+EVXewOei2gWTumRORp3FGX0UishlnNeR04DkRuQHYCHzdPf1V4EKgEqgHrgdQ1WoR+RWwwD3vblWNW+M+UU2pKdMOy8/P17q6yP/Td2Z2Dy69HGhu4Q/zVrNuVx03nzmMEwcX0NKqzi9VWlqhtbWV5lZoaW1tO36wuZXPNu/l4/XVbK89SJbAcQN6cuqQQsYM7k3XbE/be6zYuo97563m+gklTBhW5DcOf21qxg2NvIxXuiS1WBLgvitOPCRhhTp/QEGe3zqWxQV5vD/t7I7HJFKvqon7aSYBLMEZS3BppLG5lfvfWMPq7bV854yhjC2JvCO2omyqrufj9dUsWF9NdX0T2VnC6EG9OLWkkBMGFjDr3XWs2lbLjMtHH9a1+8mPNgTcm3bjl4ZElOTufW0lK7btj/gzpLtidxtAuIWXiwvy2FLTQKDv1t7nOzJtaQkuDViCi5wluPTQ2NLKn95cw/KttREnkkBUlZc/3cK85ds52OzcT/JkgbcDTWF+LqMG9mTJ5n1U1zWS6xEaW4J/z8jJgh55uSFHdj95fjE1Dam5RcUjQkscvzf+4YoT+dGzi8M6Ny/Hw28uOYEZc1f5TYgChyQ+7/mRJrlUTXAi8oaqnhPqmD8hN3qLyEgRecNbnkVERonIf0cfrjEmUs2trTxUvpblW2u5bnxJTJIbwEfrq3lt2RfJDb5IbuA0EC1ftautoWio5AbQ1MohDUgf/WD9YSsi/9/LS1M2uQFcddogencLb+WoJ8rWQeFc5RHh0pOdVZZTJ5WSl+M55Pn2yQ1St9RXpESkq1v5pEhEertlwQpFpIQw986FHMGJyNvAVOCvqjrGPfaZqh7foejjxEZwkbMRXGprbm1l5jvr+GRTDdecNpiyGBQ89r1/lkgegZH9uqf0tOSEYYU89e3xzK6oYuoLn9IURlKPVKQrMAvyctrKhPkuSgk0xSnA+ghrZqbaCE5EbgV+BAzA2V7g/ZlgH/A3Vf1TqNcIZxVlN1X9uF2Dw9T90cuYDOCbgHI9WTS2tHLFKYOCJjffa7KA9t8+83M9nDKkNwvW70nago4WJaWTG8CG3U7S8E7xeRNKQbccVGnbLtARkW4vqGlo4o6XlvKbS044ZEHJhOlv+k1yqVjqK1Kqej9wv4j8QFX/GM1rhJPgdonIMNyRsIhcBmwNfokxJlrz1+3m8Q830ujOFTa2tJIl0KPdkv5gozB/3z7rGltSpnBxKvMtdNx+EzbAkGmvBFzsEU/eqUffeM46ui9Pzd902D24qZNKEx9gnKjqH0XkdKAEn5ylqo+HujacBHcLMBM4WkSqgPXANdGFakznFe6y+pcqqtqSm1erwiPvrWfWe+v9js5M7IQa/QSbGow33/edXVHFi4uqDkluAm337DKFiDwBDAMWA96pBwU6nuBUdR0wUUTygSxVre1ArMYkRKz2aMUyHt9RWXVdI7N8EtYZpUVcc1pJ23P+tLb73cReOKOfqZNKw96/FmuCk9gAbn/u08NWeirw1sqdCY8rzsYCx2oUS/5DJjgR+UW7xwCo6t2Rvpkx8eZv03B1XSOPf7gR4JAkl6gkOH/dbh55b33AxNQKlK/axQeVu5kyvoTsLKE5VoUOTUjeLQHFYe4h8z7vL8HEm0LI7QUp2kuuIz4DjiSKW2PhTFH6LknsCnwFWBHpGxkTrmgTT/tRkq/GllZmvbeelyqquMT9BtV+ROUvCQbz5EcbeGfVLlrhkFGYb/z5uR4ONLWENepqbFFmpVD9xUzXkQogk8cUc1uQRBNqY3Y8ZcICk3aKgOUi8jHQ1j9JVS8KdWE4U5T3+j4Wkf8F5kYRpDGHaZ/MRg3syQeV1WEnHm9R3nC/kXhfL8cjhyXCxpZWXnKnf0Il2PYVOLyjsO17D7B2Z33ba3em8lPpJBYLMcIpnVUy7ZUOvUekMm2BieuuaC+MuJKJWwV6gaoOj/ZN48n2wUUuWfvg5q/bzaMfrMfPgMuvstKitooa+bkemlv1kA3KseJdlm/SU2F+rt/7mB4RWlVjVoW/feV/OLSKyOyKqrCrlcRSuFOt7aXaPrhYCOce3FK+2CzvAfoCdv/NhBRqqvGJ+RvDTm7AIUvc4zkysuSWvnI9wiVjig+bqo62fFUw7ffJtU+cd81JfAd0SHyXgXgTkVq+yEG5QA5Qp6o9Q10bzj24r/h83QxsV9WYbPQWkfOB+3ES5yxVnd7u+S44S0FPBnYDV6jqhli8t4kvf6sGfaca56/bHZfRl8l8edlZNPj5tyPAFJ8yZv/+bFvc+6b52ycHzuguFhvCo+Vvz1y6UtUe3q/FWeV4MTAunGsDTlG6NcCCvWmHeviIiAdYDZwLbMbpD3SVqi73Oed7wChV/a6IXAl8TVWvCPa6NkUZuVhPUYZaNWhMtHyLTIeaIZh4bL9khRmwwkgiRVquK52mKEWkwls6MphgI7hFOMNCfzVBFRgaZWxepwKV7j473M6vFwPLfc65mC9uML4A/ElEJJr9ECY2Qn1T8Y7cLLmZWOqSncU3xx11yL+1cUP7JHVvYzCpsFQ/U1ZTisglPg+zcPbFHQjn2oAJTlWHdDCuUIqBz30eb8Zpbe73HFVtFpG9QB/gkHpDInITcBNAbm5uvOLt9AJtVq7cWdu2SdlfFQ5jwtW/VxcONmtM9iYms4h4MqudQMatpvyqz9fNwAacwU9I4dyD866cHIGzDw4AVX0n/PjiS1Vn4pQTIz8/30Z3cRIoeZWv2sXwvj0YN7RPwqvTm8Qq86m44m/fob/2LeHIz/Vw1amDU3ZEFqlkVjsBYr6gJplU9fporw1nFeWNwK3AQJxaYOOAD4GO9kivAgb5PB7oHvN3zmYRyQZ64Sw2MUkQLHm9VFFF5U6r4pYJcj1yyGKNQLzPt5+y9nds3NA+fjuB53qymDL+qIxJbF5fVDtZTBy67QSVJZmxetJLRAYCfwQmuIfeBW5V1c0hrw2jH9xS4BRgvqqeKCJHA/+jqpcEvTB00Nk4i0zOwUlkC4BvqOoyn3NuAU7wWWRyiap+Pdjr2iKTyIWayvFX/spkjlyP8JerT07Ie6VajdB48S5wSdZikz9ccWLG7IMTkXnA/wFPuIeuAa5W1XNDXRvOFOUBVT0gIohIF1VdKSIdntx176l9H6cqigd4RFWXicjdwEJVnQM8DDwhIpVANXBlR9/XBOevssi7q3cl/KdQkzhTxpck7L1SeWFIPCRrsUm8tgiIyG3AjTgz0UuB64H+wDM46yMWAd9U1cYYbvPqq6qP+jz+u4j8KJwLw0lwm0WkAJgNzBORPcDGKII8jKq+Crza7tgvfL4+AFwei/cyoflbRGL9wzJXuFORJnrJWmwSj8QqIsXAD3Eq+zeIyHM4g44LgftU9RkReQi4AXjQ/X2Pqg53Z+B+CwTd5hXAbhG5BnjafXwVYd6qCqcW5dfcL+8Skbdw7oP9J4ogTYqzFZCZK9MWcaSLqZNKk1KuK45bBLKBPBFpArrhVPg/G/iG+/xjOFu7HiR227y+hXMP7j6ckeMHOCPHsIINSkQeAJ5R1Q9U9e0IA0u4wsJCysvLkx1GyqppaGL73gM0trSS68miX6+ueNwWSNcPrU9ydCYQAY7q09HbI1to2LQlFuGYEMp3OA1XCoDbT4hJ4aewZYlQ3Lslmu+D2SKy0OfxTHeFOgCqWuUW298ENACv4UxJ1vhUt9qMs70LwtzmFYqqbgRCdg7wJ5wpykXAf7v33f6Bk+wWhrgmaaqrqykrK0t2GClpdkUVd7yxlIamLJz9kiA0ojgFag82dbGFJCnomCO7c/t5Ryc7DBOBMp8qKvf8vpw1OxKz8E2Aq8cN5pYLTojm8mZVHRvwtZ3tYhcDQ4Aa4Hng/GjeKBIi8hjOqskanzjuVdVvhbo2nCnKx4DH3NJdlwK/FZHBqjqig3GbBJsxd9Vh+3K8cwW2fy01eLLg+tOH2FRihphdUcWGXYmbGYlzR++JwHpV3QkgIi/hLN0vEJFsdxTnu90rVtu8RnmTG4Cq7hGRkGW6wPtjfHiGA0cDRwErI4vPpIJUKB9kAsvP9VhyyzAz5q6iKcHd2eP4/3wTME5EurlFj8/BKa34FnCZe861wMvu13Pcx7jPvxllmcUsd9QGtNVJDqtISTj34H4HfA1Yi7MU9Fe+2dSkj2SXDzKH8q0KYjJTMn6ojNcCE1X9SEReAD7BKZlVgVNB6hXgGRH5tXvsYfeSWG3zuhf4UESedx9fDtwTzoXhZMG1wHhVtfXiaW7qpFKmPv9pwn+iNI7sLOGhaxKzodqkhkT/UBnvGpSqeidwZ7vD63CK57c/NybbvFT1cXfxi7d61iW+XWeCCece3F87EpxJvBzdULIAACAASURBVKv/9iHvr/2im9GEYYU89e3xAJ2yyn+g+1q+m9qzCP/PxrcCR7hVXjxZcN3pJVHFb9LXWUf35cn5mxLyXtF28k4HbkILK6n5ClmqK9109lJd7ZOb14RhhWzY3dBppigL83M7VA7q0ffX8/7aQ++Hh6qb6Jsw83M9gNN5PJNLUhn/klGqa0MEvd/8SdVSXR0R1o06kz78Jbdgx5PN2Z7QEvH2hGAjrsL8XH536aio4mlubeXZBZ/z/trdDOqdx/6DzeypbworSXW2MlQmtFjegwvWqcG7l9UcKtx2OScBX8L5831fVT+Ja1SmU8jP9fC7S0f5bbuSJRDoVqF3JAUcdl2uJ6uton2k9jY08rd317NyWy2TjuvHpScNJMu+cZgOCHUPzpu0QrUZKi7I4/1pZ1My7RW/z7dk2ExcrITcJiAiv8Apv9IHKAIeFZH/jndgJnKzK9p3G0oP44b2Ycr4oyjMd5rVFubn8q0JQ7jxS0Pajnn/oRbm57ZNE/q7LtrWK0ur9nLXnOWs3bmf6yeUcPnJgyy5mQ6bOqmUvBxPwOcHFORxzbjBQV/Dd+FIcYAVkgV5OUyY/iZDpr3ChOlvpu33An9EZJyILBCR/SLSKCItIrIvrGvDaJezChjtrohBRPKAxaqaku1iO/M9uGS15uiIWVMCFk5IiMaWVl5ctJk3Vu6guCCP75wxNJ51/EwnMdGnksnsiqqo61H27pbDnV89rm3hyOyKqsMaqeZkCQg0+bT8yMvxRNz0NFXvwbkrKK/EqZwyFpgCjFTVO0JdG85G7y34dPIGunB4Y1KTZLMrqtIuuXlHXpHaXddI5Y5aOrpAqqqmgXteWcEbK3cw8Zh+/PzLx1hyMzE3eUxxwJFXKAeaDr3TPHlMMb+55ASKC/IQnBFd967ZhyQ3gIamFmbMXRVtyClHVSsBj6q2uK1zwioRFs49uL3AMrfpnALnAh+7RZhR1R9GGbMJw+yKKmbMXcWWmgYGBFgG/N+zl/JUgpYix0q098qaW1v5/bxVbN93kKLuuXxpeBGnDyuKKFkqSvmqnTy74HPycjzces4ITijuFXEsxoQr2u0C3kTl+39+8pjiQx4PCXBfLoMqF9WLSC6w2C08spUwq3CFk+D+4f7yKo84PBOV9tMRVTUN3PHSUuCLlvT/PXtpwvbZdESuR+jeNafDnZznLd/O9n0HufD4I1m3q47Zi7cwe/EWjhvQkwnDizhxUAG5nsD/9msPNvP39zfw6eYajhvQk29NKKFXXnQjSWPCMbuiiqc/+jzq60MlqkALWTJoNuKbOAnt+8BtOPUtLwnnwnCLLZsk8Fcc2fcnuvRJbsH3j4Wruq6Rfy7ZyuiBBVxy0kAAdu0/yHuVu/igchcz31lHt1wP44YUMmFEEUcVHno7YcXWfcx6bx11B1u44pRBTDz6CMQWkpg48v6Q2pFVjqES1dRJpYfdl4t3RZMEm6yq9wMHgF8CiMitwP2hLgxnkckI4DfAsfjci1PVoR0IOG7SdZHJr/+1vG2TsHeEM+u99ckOq8Niucn5obfXsvjzGn49+XiKunc55LlWVVZs28d7a3ZTsWkPza3KoN55fGl4EWNLejNv+Q7+s2wb/Xp24aYzhh6W/IyJpVht9M7xCDMuGx1ysUg4tzJCSeFFJp+o6kntjlWoasiOAuEkuPdwao/dB3wVp5Nqlqr+IvqQ4ycdE9zsiip++sKSjOmmnQWcEeNCwsu37uP381Zz0egBXDR6QNBz6w4289GGat5bs5NN1V98czljRBFXnDKILtmBl20bEwveBDdk2itB97eFUpCXw+I7z4tNUCGkWoITkatwOoV/CXjX56keQKuqnhPqNcK5B5enqm+4rcY3AneJyCIgJRNcOpoxd1VaJbcu2VmMH1bIB5W7aXRXbwlwZpyq4ze3tvJ/H22kqHsu5x9/ZMjz87tkc3bpEZxdegSfV9ezcOMehhTlc+KggpjHZkwwHS22vLehKYbRpJ0PcBaUFOF0FPCqBZaE8wLhJLiDIpIFrBGR7+NsEegeYaAmiHRa7eTb4iVRrV7mLd/Otn0H+eE5w4MuIPFnUGE3BhV2i1NkxgTn7/5YJDJooUjE3AHVRmB8tK8RzneLW4FuwA+Bk3FWtFwb9AoTkXT6R5zo/mXV9V8sLBlVbCMwk168+9YK8nIivjYnSzJpoUjUOlLJJGSCU9UFqrpfVTer6vWqeomqzu942MbrrKP7JjuElPXcws9pbVWuOnVQskMxJiqTxxSz+M7z+MMVJ7Zt0O7dLYeCvJy2zdrXjBtM725fJMGCvBxmXB56cUkn8SfgKmANkAfcCPw5nAvD6eg9EpgKHOV7vqqeHfAiE5G3Vu5MdggpacXWfSzcsIeLRg84bNWkMemm/Qbt9n49+YQERpNeVLVSRDyq2oJTD7kCCFmqK5x7cM8DDwF/A6KbSDZBpdM9uERpbm3lqQgWlhhjMlZcK5k0q+qDHYnOBJfotvbR8jbxTITXO7CwxBiTUfxVMrk0nAsDfucQkUIRKQT+KSLfE5H+3mPucRMjUyeVYvU0vlBd38icJVsZPbCXLSwxJoWISIGIvCAiK0VkhYiMd3PCPBFZ4/7e2z1XROQBEakUkSVuX9GIuaspewBdVPWXqvpjt/hySMFGcIv4ohcfOPfh2t4TSMlKJqkqUKUB7/F0aFcYadftaD3ftrAkeJ8sY0zC3Q/8R1Uvc6cNuwH/BbyhqtNFZBowDfgZcAEwwv11GvCg+3tYxKmjdyfOyC3LPdQM/FFV7w7nNQImOFUdEm4gJjhvtX9vEvMWTV64sZoXF1VFvUcm0aJtbxOJFVv3sWDDHi4a3d8WlhiTQkSkF3AGcB2AqjYCjSJyMVDmnvYYTkH+nwEXA4+rUy5rvjv666+qW8N8y9uACcApqrrejWEo8KCI3Kaq94WMOVCpLhE5BfhcVbe5j6fgzHtuBO5S1eowg0yoQYMG6RNPPJHsMNrUNDTxeXW93+cEQdNi7OYM4/t070L3LuHcto2OomypOYAqFBd0tULIJm316Bq//yfxctZZZzUCS30OzVTVmd4HInIiMBNYDozGmeW7FahS1QL3HAH2qGqBiPwLmK6q77nPvQH8TFUXhhOPu1LyXFXd1e54X+C1cGpRBvtb+Csw0X3BM4DpwA8A74e8LJwgE626upqysrJkh9HGKbaafv/Y27vxS0M4OgYFk4OZu2wrzy+u4gdnD6fbQLv3ZtJXmU9H7zTSrKpjgzyfDZwE/EBVPxKR+3GmI9uoqopIrH5qz2mf3Nz32CkiYe2cD7Y8zeMzSrsCJ5u/qKr/DxgeeaydUzpsAcjP9QRcISk4yS0W3QCC2VPfyMufbmVUcS9GW3IzJhVtBjar6kfu4xdwEt52EekP4P6+w32+CmfFo9dA91i4GqN8rk2woYVHRLJVtRk4B7gpzOuMj3TYAlDX2MKsKWOZv243T3+8qW0xSX6uh6tOHRx2clu0sZp5y7fTMy+Hvj260LdHF47o0ZW+3btQmJ+DJyvwz1PPLdxsC0uMSWGquk1EPheRUlVdhZMXlru/rsWZ5bsWeNm9ZA7wfRF5Bmdxyd4I7r8BjA5Qkkvwad0WTLBE9TTwtojsAhpw2xWIyHBgbwRBdmpTJ5Xyo2cXJzuMoLyLR8YN7RP1SO29Nbt47MMNHNGjC7UHm1myeS/NrV/MVGSJ8z5H9OhCUY8uHNHdSYBFPbpQU9/Egg3VfHVUf/r2sIUlxqSwHwBPuSso1+G2TwOeE5EbcNZofN0991XgQqASqHfPDZuqdnjjbdB+cCIyDuiPc0Ovzj02Euiuqp909M3jIRX7wZVMeyXZIQQUi27b81Zs59kFn3PcgJ7cUjac3OwsVJU99U3s3H+QnfsOOr/XHmTH/oPsqj3I/oPNh7xGUfdc7r74eNvUbTLCxDS8B5dq/eBiIehUo7+iyqq6On7hZCYR6EDH+qjlerI4fXghSzbva+sUPmpgz0Med6TbtqK8smQrsxdv4aTBBXz7jKHkuNOQIkJhfi6F+bmU9utx2LX1Tc3sqnWS3q79Bzmmf09LbsaYmLJ7aQmQnOQmX4zM2m+tDHurZWCK8sKizcxdtp3xQwu57vSSoPfY2uuWk83gwmwGF2bUD4zGmBRiPzInQHES+r01t2jcVj6qKk/O38jcZdspK+3LtyYMiSi5GWNMIiTlu1Kg2mV+zvuPiNS4GwbT1tRJpeR4ErtpuTVOr9vS2srD76/n7dW7OP+4I7n6tMG2IdsYk5KS9WP3NJzaZSOAN2i3WdDHDJxK0mkvPzexs8Hx+Ittam3loXfWMX9dNV8bU8xlJw9ErEy0MSZFJSvBXYxTswz398n+TlLVN4DaRAUVD7MrqrjjpaXUNDQl9H3PKC2K6esdbG7hj2+soWJTDVedMogvn9A/pq9vjDGxlqwE189nw982oENrakXkJhFZKCILm5ubQ1+QQL/857KYF1P2ne3Mz/VwzJHd2/4is4Cy0iKuOa0kZu9X39TMH15fzYqttVx3egnnHJN+S6CNMZ1P3ObNROR1wF8r5p/7PohF7TK3IOhMcPbBdeS1Yml2RRV76mM7cps1JVipuNirPdjMffNWsXlPA985YyhjS6wVoDEmPcQtwanqxEDPich2b9uEdrXLMsqMuauSHUKH1DQ0cu9rq9lZe5AfnD2CE4p7JTskY4wJW7KmKOfg1CyDQ2uXZZR0KLQcyK79B5n+75VU1zXyo4kjLbkZY9JOshLcdOBcEVmD05JnOoCIjBWRWd6TRORd4HngHBHZLCKTkhJtlAbEeP9bov6ytu5tYPq/V1Lf2MLt543k6CMPr0RijDGpLimVTFR1N04l6vbHFwI3+jz+/xIZV6xNnVTKHS8tjdkik1ivjPRnSVUNj763AcSJf1DvbnF/T2OMiQcr1RVHk8cUA3D7c5/S0oF6XVk4yS2WKyPbqz3YzDMfb+Kj9dUMKOjK98qGcWTPxFdgMcaYWLEEF2eTxxRzW5TtchLRaFRRFm7Yw/99tIm6xma+Oqo/Xx7Vn2wrvWWMSXOW4BIgLyeL+qbIi2fFO7ntbWjkifmbWPx5DSV9unH7hJEMLLApSWNMZrAEF2ezK6qiSm7xpCjvV+7m2QWbaGpRLjupmHOP7WcFk40xGcUSXJyl2l64XfsP8viHG1i+tZYRR3Tn2tOPsnttxpiMZAkuzqqi3AuXG+PuA6rKW6t28sInmxHg6tMGUzayr3UCMMZkLEtwKWrK+JKYvdbWfQ08/sEG1uyo47gBPfnm+KMoyu8Ss9c3xphUZAkuBZWVFsVkgUlLayuvLd/Oy4u3kJudxfUTSjh9WB9rcWOMiZqIeICFQJWqfkVEhgDPAH2ARcA3VbVRRLoAjwMnA7uBK1R1QyJjtVUFKSY/1xOT/W6f76nnf15dyYufVDFqYC9+dfFxTBhWZMnNGNNRtwIrfB7/FrhPVYcDe4Ab3OM3AHvc4/e55yWUJbgUU9fYsaonTa2tzF5cxa/+tZzq+ka+e+ZQvlc2nF55uTGK0BjTWYnIQODLwCz3sQBnAy+4p/j29/Tt+/kCTsnFhP6EnXFTlIWFhZSXlyc7jDa3nxBZf7rsrCwaNi2N6r0ONrewa38jpdrKySdn0zs/C49U0bCpKqrXM8ZEp3zHitAnpZ5sEVno83im24rM1x+AnwLeArV9gBpV9X6j2wwUu18XA58DqGqziOx1z98Vj+D9ybgEV11dTVlZWbLDaHPdtFfCPjfXk8WU8UcxYnBk99+aW1t56ZMq5i3fTkG3LkwZX8Igq/5vTNKUHZuWTYGbVTVgw0kR+QqwQ1UXiUhZ4sKKXsYluFRTXJAX9laBKeOPinhxyZ76Rh4sX8u6XXWcMbKIy08eSF6O/bUaY2JuAnCRiFwIdAV6AvcDBSKS7Y7iBgLeKaMqYBCwWUSygV44i00Sxu7BxdnUSaVkhTnrHGlyW7mtlrv/tZyqmga+e+ZQpowrseRmjIkLVb1DVQeqaglwJfCmql4NvAVc5p7m29/Tt+/nZe750Vedj4J9NwzT7IoqZsxdxZaaBgYU5DF1Umlbt4BgvOf8KMqCy/4oymvLtvPiJ5vp26MLP51USv9eVo3EGJMUPwOeEZFfAxXAw+7xh4EnRKQSqMZJigklCU6ocZefn691dXUxfc3ZFVWH9XXLy/Hwm0tOCCvJAQyZ9gqh/qRnTQk4/d3mQHMLf/9gAws37OGkwQVcP8FGbcakmolpeA9OROpVNT/ZccSSTVGGYcbcVYc1LW1oaomozuTV4wZ3OI6t+xq455UVLNqwh0tPKubmsmGW3IwxJgBLcGHYEmCRSCR1Jn89+YSgz+fneoI+/8mmPdzzrxXUHmjmx+eO5ILj+9umbWOMCcJ+/A/DgAArIQVn+jLYNKUzvbmEhihb5rSq8o+KKv792TZK+nTj5rLh9Mm3TdvGGBOKjeDCcNbRff0eV4K3w5ldUcWPn10cVnLzV8Gk9mAz972+mn9/to0zRhTxswuOtuRmjDFhshFcEN6Vk8GmIqtqGgKO4mbMXUW447bCdolrw+46/lK+ln0NTVw3voQvjSiKJHRjjOn0LMEF4G/lZCB3vOSU1po8pviQ7QSRrE8dNbBn29fvrtnJUx9tomdeDtMuOJqSPhm1sMkYYxLCElwA/lZOBtLQ1MLtz33Kwo3VvLioKuzrfC1Yv4evjx3M0x9v4t01uzi2fw++fcYwenSxvyJjjImGffcMINDKyUBaVHlq/qaIRm2+6hpb+N1/VrJhdz0XnnAkk08sJsu6bRtjTNQswQUQaOVkMB3dMr997wFuKRvGmMG9O/hKxhhjbBVlAFMnlZKXc+jetLwcD9eMG3zY8VgQ4OdfOcaSmzHGxIiN4ALwror0V39y7FGF3P7cp7TEqMyZ4HQSOLKn1ZM0xphYsVqUUYpklWUwvbrmcNdFx9Kja06MIjPGJJvVokwNNoILIVAXgfYjvCyRiEZ0Rd1z+dM3TmprkfP68u1xid8YYzorG8EFEUkXgXC6BXjlerJ456dncWSvrm3HLMEZYzqqIyPHTBzB2SKTICLpIjCgIPz7Z5eeXHxIcjPGGBN7luCCCLQXzt/xSDp3v7N6V0fCMsYYEwZLcEEEGpUFOt4a5hxlpPvrjDHGRM4SXBCB9sJNnVR62LmRND81xhgTf7aKMohge+Hai7S0lzHGmPiyEVwIk8cUM3VSKQMK8thS08CMuauYXVHV9vzsiiomTH+zw2W6jDEmlYnIIBF5S0SWi8gyEbnVPV4oIvNEZI37e2/3uIjIAyJSKSJLROSkRMdsI7gQ2m8VqKppaGuPA8Rks7cxxqSBZuB2Vf1ERHoAi0RkHnAd8IaqTheRacA04GfABcAI99dpwIPu7wmTlAQnIoXAs0AJsAH4uqruaXfOiTh/ID2BFuAeVX02sZEG3irwo2cX44lwc7cxxqQrVd0KbHW/rhWRFUAxcDFQ5p72GFCOk+AuBh5XZ7P1fBEpEJH+7uskRLJGcNPwn/F91QNTVHWNiAzA+WlhrqrWxDOw9huug614jDa5Zfl5H2OMSRciUgKMAT4C+vkkrW2Ad7d5MfC5z2Wb3WMZn+ACZfw2qrra5+stIrID6AsETXCFhYWUl5dHHFBNQxPb9x6gsaWV7KwsCrrl0L1LNj8Z1UI8qr00bFoa+iRjjIlA+Y4VHbk8W0QW+jyeqaoz258kIt2BF4Efqeo+8elbqaoqIikzrZWsBBco4/slIqcCucDaAM/fBNwEkJubS1lZWUTBzK6o4o43ltLQlIV33U2uRxnWN4cV22LfGqcwP5ffjTkh5q9rjOncyjpW5LlZVccGO0FEcnCS21Oq+pJ7eLt36lFE+gM73ONVwCCfywe6xxImbqsoReR1EfnMz6+Lfc9z52cDZnz3D+wJ4HpVbfV3jqrOVNWxqjo2OzvynO3vPltjSysrtu2P+LXCcYmfbQbGGJPKxBmqPQysUNXf+zw1B7jW/fpa4GWf41Pc1ZTjgL2JvP8GcRzBqerEQM+JSKCM3/68nsArwM9VdX6cQk34HjZvBwFjjEkjE4BvAktFZLF77L+A6cBzInIDsBH4uvvcq8CFQCXOmorrExtu8qYovRl/Oodm/DYikgv8A2cVzgvxDGZAQV7CymeVlRYl5H2MMSaWVPU9nP7M/pzj53wFbolrUCEka6P3dOBcEVkDTHQfIyJjRWSWe87XgTOA60RksfvrxHgE468kV7xcc1pJQt7HGGM6u6SM4FR1N/4z/kLgRvfrJ4EnExGPt/TW7c99avvajDEmQ1ipLtfkMcWW3IwxJoNYgnP51pc0xhiT/izBuX7775XJDsEYY0wMWYJzbd13IO7vYSsojTEmcSzBuYoDdOmOJVtBaYwxiWMJzuVvq0CuJ4tcT6BtH8YYY1KZJTjX5DHF/OaSEyjMzwWcepFTxh9FY4utrDTGmHRkDU99TB5TTPcu2cxft5uXKqqY9d56sgC/BTCNMcakNEtw7cxft5vHP9xIY4uT1mKV3GyobIwxiWXfd9t5qaKqLbnFko0CjTEmsSzBtVNd1xiX1/Xe2zPGGJMYluDaiUciyvVkWQ84Y4xJMEtw7VwypphcT3h/LOGc5V2NaT3gjDEmsWyRSTveRPRSRRXVdY0U5ucyamBPPqisPuTeXK4ni9OHF/o9bgnNGGOSzxKcH+OG9jksQQ3v2+OQpHfJmGLGDe0T8LgxxpjkEs2wFjH5+flaV1cX9fWvL98ew2iMMSZxJh7bL+prRaReVfNjGE7S2T04Y4wxGckSnDHGmIxkCc4YY0xYROR8EVklIpUiMi3Z8YRiCc4YY0xIIuIB/gxcABwLXCUixyY3quAswRljjAnHqUClqq5T1UbgGeDiJMcUVMZtE6ivr1cRaQjz9GygOZ7xpDD77J2TffbOKZzPniciC30ez1TVmT6Pi4HPfR5vBk6LUXxxkXEJTlXDHpWKyEJVHRvPeFKVfXb77J2NffbO99ltitIYY0w4qoBBPo8HusdSliU4Y4wx4VgAjBCRISKSC1wJzElyTEFl3BRlhGaGPiVj2WfvnOyzd04d/uyq2iwi3wfmAh7gEVVd1uHI4ijjSnUZY4wxYFOUxhhjMpQlOGOMMRmpUyS4UOVlRKSLiDzrPv+RiJQkPsr4COOz/1hElovIEhF5Q0SOSkac8RBuWSERuVREVEQyYhl1OJ9bRL7u/r0vE5H/S3SM8RTGv/nBIvKWiFS4/+4vTEacsSYij4jIDhH5LMDzIiIPuH8uS0TkpETHmHCqmtG/cG6GrgWGArnAp8Cx7c75HvCQ+/WVwLPJjjuBn/0soJv79c2d6bO75/UA3gHmA2OTHXeC/s5HABVAb/fxEcmOO8GffyZws/v1scCGZMcdo89+BnAS8FmA5y8E/g0IMA74KNkxx/tXZxjBhVNe5mLgMffrF4BzREQSGGO8hPzsqvqWqta7D+fj7G3JBOGWFfoV8FvgQCKDi6NwPve3gT+r6h4AVd2R4BjjKZzPr0BP9+tewJYExhc3qvoOUB3klIuBx9UxHygQkf6JiS45OkOC81depjjQOaraDOwFMqEtdzif3dcNOD/hZYKQn92dohmkqq8kMrA4C+fvfCQwUkTeF5H5InJ+wqKLv3A+/13ANSKyGXgV+EFiQku6SL8fpL3Ovg/OuETkGmAscGayY0kEEckCfg9cl+RQkiEbZ5qyDGfE/o6InKCqNUmNKnGuAv6uqveKyHjgCRE5XlVbkx2Yia3OMIILp7xM2zkiko0zbbE7IdHFV1ildURkIvBz4CJVPZig2OIt1GfvARwPlIvIBpx7EnMyYKFJOH/nm4E5qtqkquuB1TgJLxOE8/lvAJ4DUNUPga5AUUKiS660K7XVUZ0hwYVTXmYOcK379WXAm+relU1zIT+7iIwB/oqT3DLpXkzQz66qe1W1SFVLVLUE5/7jRaq60P/LpY1w/r3Pxhm9ISJFOFOW6xIZZByF8/k3AecAiMgxOAluZ0KjTI45wBR3NeU4YK+qbk12UPGU8VOUGqC8jIjcDSxU1TnAwzjTFJU4N2mvTF7EsRPmZ58BdAeed9fVbFLVi5IWdIyE+dkzTpifey5wnogsB1qAqaqaCTMW4X7+24G/ichtOAtOrsuEH2hF5GmcH1yK3PuLdwI5AKr6EM79xguBSqAeuD45kSaOleoyxhiTkTrDFKUxxphOyBKcMcaYjGQJzhhjTEayBGeMMSYjWYIzxhiTkSzBmYzmdgl40udxtojsFJF/Rfl6BSLyPZ/HZYFeS0TKM2DjuDFpyxKcyXR1wPEikuc+PpeOVW8owOk+YYxJcZbgTGfwKvBl9+urgKe9T4hIoYjMdvtjzReRUe7xu9z+WuUisk5EfuheMh0YJiKLRWSGe6y7iLwgIitF5Kn2nShE5Fsi8gefx98WkfvaByki+32+vkxE/u5+fbmIfCYin4rIO+6xEhF5V0Q+cX+d7h7PEpG/uLHME5FXReQy97mTReRtEVkkInMzvZK8MZbgTGfwDHCliHQFRgEf+Tz3S6BCVUcB/wU87vPc0cAknBYsd4pIDjANWKuqJ6rqVPe8McCPcHqLDQUmtHv/54CvuteDU0HikQji/wUwSVVHA94qMzuAc1X1JOAK4AH3+CVAiRvLN4HxAO57/xG4TFVPdt//nghiMCbtZHypLmNUdYk4XdqvwhnN+foScKl73psi0kdEvL3CXnGLTx8UkR1AvwBv8bGqbgYQkcU4CeY9n/ffLyJvAl8RkRVAjqoujeAjvA/8XUSeA15yj+UAfxKRE3HKbY30+TzPu5Xxt4nIW+7xUpzi0vPcAaYHyOg6hMZYgjOdxRzgf3Fq9YXb68+3s0ILgf+/hHPeLJwR4krg0QCv41s3r2vbQdXvishpONOsi0TkZJweZtuB0TgzMaEatgqwTFXHhzjPmIxhU5Sms3gEd7B8UwAAAUBJREFU+KWfkdO7wNXgrIgEdqnqviCvU4vTaiciqvoRTquSb+BzD7Cd7SJyjNur7mvegyIyTFU/UtVf4FS9H4TT0mmrO1L7Js6IDJzR3qXuvbh+uF0DgFVAX7f/GSKSIyLHRfo5jEknNoIznYI7hfiAn6fuAh4RkSU4Fdav9XOO7+vsFqcT9mc43c8j6Qb+HHCiqu4J8Pw04F84SWwhTpcHgBkiMgJnFPYG8CnwF+BFEZkC/AdntSjAizitYJbjdG/+BKctSqO72OQBEemF83//D8CyCOI3Jq1YNwFjEsTdL3efqr4R5/fp7t736wN8DExQ1W3xfE9jUpGN4IyJMxEpwEk0n8Y7ubn+5b5nLvArS26ms7IRnDHGmIxki0yMMcZkJEtwxhhjMpIlOGOMMRnJEpwxxpiMZAnOGGNMRvr/ASd0FkTw3fERAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 364
},
"id": "YRcyx4Wmuqwl",
"outputId": "e7d8ffca-12c0-4b2e-e687-57c187ae5167"
},
"source": [
"# Ad spend is very redundant with Monthly usage and Last upgrade.\n",
"shap.plots.bar(shap_values, clustering=clust, clustering_cutoff=1)\n"
],
"execution_count": 11,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "8ofDNeXc1vLr"
},
"source": [
""
],
"execution_count": 11,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "o_O-kamvu6nH",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 249
},
"outputId": "9159d17d-8610-4fda-d654-cb1721bd6c9d"
},
"source": [
"from econml.dml import LinearDML\n",
"from sklearn.base import BaseEstimator, clone\n",
"import matplotlib.pyplot as plt\n",
"\n",
"class RegressionWrapper(BaseEstimator):\n",
" \"\"\" Turns a classifier into a 'regressor'.\n",
"\n",
" We use the regression formulation of double ML, so we need to approximate the classifer\n",
" as a regression model. This treats the probabilities as just quantitative value targets\n",
" for least squares regression, but it turns out to be a reasonable approximation.\n",
" \"\"\"\n",
" def __init__(self, clf):\n",
" self.clf = clf\n",
"\n",
" def fit(self, X, y, **kwargs):\n",
" self.clf_ = clone(self.clf)\n",
" self.clf_.fit(X, y, **kwargs)\n",
" return self\n",
"\n",
" def predict(self, X):\n",
" return self.clf_.predict_proba(X)[:, 1]\n",
"\n",
"# Run Double ML, controlling for all the other features\n",
"def double_ml(y, causal_feature, control_features):\n",
" \"\"\" Use doubleML from econML to estimate the slope of the causal effect of a feature.\n",
" \"\"\"\n",
" xgb_model = xgboost.XGBClassifier(objective=\"binary:logistic\", random_state=42)\n",
" est = LinearDML(model_y=RegressionWrapper(xgb_model))\n",
" est.fit(y, causal_feature, W=control_features)\n",
" return est.effect_inference()\n",
"\n",
"def plot_effect(effect, xs, true_ys, ylim=None):\n",
" \"\"\" Plot a double ML effect estimate from econML as a line.\n",
"\n",
" Note that the effect estimate from double ML is an average effect *slope* not a full\n",
" function. So we arbitrarily draw the slope of the line as passing through the origin.\n",
" \"\"\"\n",
" plt.figure(figsize=(5, 3))\n",
"\n",
" pred_xs = [xs.min(), xs.max()]\n",
" mid = (xs.min() + xs.max())/2\n",
" pred_ys = [effect.pred[0]*(xs.min() - mid), effect.pred[0]*(xs.max() - mid)]\n",
"\n",
" plt.plot(xs, true_ys - true_ys[0], label='True causal effect', color=\"black\", linewidth=3)\n",
" point_pred = effect.point_estimate * pred_xs\n",
" pred_stderr = effect.stderr * np.abs(pred_xs)\n",
" plt.plot(pred_xs, point_pred - point_pred[0], label='Double ML slope', color=shap.plots.colors.blue_rgb, linewidth=3)\n",
" # 99.9% CI\n",
" plt.fill_between(pred_xs, point_pred - point_pred[0] - 3.291 * pred_stderr,\n",
" point_pred - point_pred[0] + 3.291 * pred_stderr, alpha=.2, color=shap.plots.colors.blue_rgb)\n",
" plt.legend()\n",
" plt.xlabel(\"Ad spend\", fontsize=13)\n",
" plt.ylabel(\"Zero centered effect\")\n",
" if ylim is not None:\n",
" plt.ylim(*ylim)\n",
" plt.gca().xaxis.set_ticks_position('bottom')\n",
" plt.gca().yaxis.set_ticks_position('left')\n",
" plt.gca().spines['right'].set_visible(False)\n",
" plt.gca().spines['top'].set_visible(False)\n",
" plt.show()\n",
"\n",
"# estimate the causal effect of Ad spend controlling for all the other features\n",
"causal_feature = \"Ad spend\"\n",
"control_features = [\n",
" \"Sales calls\", \"Interactions\", \"Economy\", \"Last upgrade\", \"Discount\",\n",
" \"Monthly usage\", \"Bugs reported\"\n",
"]\n",
"effect = double_ml(y, X[causal_feature], X.loc[:,control_features])\n",
"\n",
"# plot the estimated slope against the true effect\n",
"xs, true_ys = marginal_effects(generator, 10000, X[[\"Ad spend\"]], logit=False)[0]\n",
"plot_effect(effect, xs, true_ys, ylim=(-0.2, 0.2))"
],
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"text": [
"pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n"
],
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 360x216 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 364
},
"id": "KGXH2KZ7v3ET",
"outputId": "108e6cec-9850-4278-958d-91717929ca30"
},
"source": [
"# Interactions and sales calls are very redundant with one another.\n",
"shap.plots.bar(shap_values, clustering=clust, clustering_cutoff=1)"
],
"execution_count": 13,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 364
},
"id": "BfNKJV3VNUkz",
"outputId": "e81e643b-b269-49d0-eec2-852b4823bf20"
},
"source": [
"# Discount and Bugs reported seem are fairly independent of the other features we can\n",
"# measure, but they are not independent of Product need, which is an unobserved confounder.\n",
"shap.plots.bar(shap_values, clustering=clust, clustering_cutoff=1)"
],
"execution_count": 14,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 232
},
"id": "FtLJeoJVN7Sh",
"outputId": "ef758010-2822-4e66-f38c-6a1607cd12e9"
},
"source": [
"# estimate the causal effect of Ad spend controlling for all the other features\n",
"causal_feature = \"Discount\"\n",
"control_features = [\n",
" \"Sales calls\", \"Interactions\", \"Economy\", \"Last upgrade\",\n",
" \"Monthly usage\", \"Ad spend\", \"Bugs reported\"\n",
"]\n",
"effect = double_ml(y, X[causal_feature], X.loc[:,control_features])\n",
"\n",
"# plot the estimated slope against the true effect\n",
"xs, true_ys = marginal_effects(generator, 10000, X[[causal_feature]], logit=False)[0]\n",
"plot_effect(effect, xs, true_ys, ylim=(-0.5, 0.2))"
],
"execution_count": 15,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 360x216 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ac-xJ2SLN9SB"
},
"source": [
""
],
"execution_count": 15,
"outputs": []
}
]
}
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