{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using Shapash with FastTreeSHAP explainer\n",
    "\n",
    "You can compute your local contributions with the [FastTreeSHAP](https://github.com/linkedin/FastTreeSHAP) library and summarize them with Shapash\n",
    "\n",
    "Contents:\n",
    "- Build a Regressor\n",
    "- Create Explainer using FastTreeSHAP\n",
    "- Compile Shapash SmartExplainer\n",
    "- Compare contributions with shap\n",
    "\n",
    "Data from Kaggle [House Prices](https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from category_encoders import OrdinalEncoder\n",
    "from lightgbm import LGBMRegressor\n",
    "from sklearn.model_selection import train_test_split\n",
    "import fasttreeshap\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapash.data.data_loader import data_loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapash.data.data_loader import data_loading\n",
    "house_df, house_dict = data_loading('house_prices')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_df=house_df['SalePrice'].to_frame()\n",
    "X_df=house_df[house_df.columns.difference(['SalePrice'])]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Classification Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from category_encoders import OrdinalEncoder\n",
    "\n",
    "categorical_features = [col for col in X_df.columns if X_df[col].dtype == 'object']\n",
    "\n",
    "encoder = OrdinalEncoder(\n",
    "    cols=categorical_features,\n",
    "    handle_unknown='ignore',\n",
    "    return_df=True).fit(X_df)\n",
    "\n",
    "X_df=encoder.transform(X_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Xtrain, Xtest, ytrain, ytest = train_test_split(X_df, y_df, train_size=0.75, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "regressor = LGBMRegressor(n_estimators=200).fit(Xtrain,ytrain)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create FastTreeSHAP Explainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "shap_explainer = fasttreeshap.TreeExplainer(regressor, algorithm = \"auto\", n_jobs = -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "shap_values = shap_explainer(Xtest).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "shap_contributions = pd.DataFrame(shap_values, columns = Xtest.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use Shapash With FastTreeSHAP Contributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapash import SmartExplainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpl = SmartExplainer(\n",
    "    model=regressor,\n",
    "    preprocessing=encoder,\n",
    "    features_dict=house_dict\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use contributions parameter of compile method to declare FastTreeSHAP contributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpl.compile(\n",
    "    contributions=shap_contributions.reset_index(drop=True), # FastTreeSHAP Contribution pd.DataFrame  \n",
    "    y_target=ytest.reset_index(drop=True), # Optional: allows to display True Values vs Predicted Values\n",
    "    x=Xtest.reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dash is running on http://0.0.0.0:8020/\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:Your Shapash application run on http://slhdg001:8020/\n",
      "INFO:shapash.webapp.smart_app:Dash is running on http://0.0.0.0:8020/\n",
      "\n",
      "INFO:root:Use the method .kill() to down your app.\n"
     ]
    }
   ],
   "source": [
    "app = xpl.run_app(title_story='House Prices Fasttreeshap', port=8020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "app.kill()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare contributions to Shap library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpl_shap = SmartExplainer(\n",
    "    model=regressor,\n",
    "    preprocessing=encoder,\n",
    "    features_dict=house_dict\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpl_shap.compile(    \n",
    "    y_target=ytest.reset_index(drop=True), # Optional: allows to display True Values vs Predicted Values\n",
    "    x=Xtest.reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "contributions = { \"fasttreeshap\":xpl.contributions,\n",
    "                  \"treeshap\":xpl_shap.contributions}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapash.explainer.consistency import Consistency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cns = Consistency()\n",
    "cns.compile(contributions=contributions)\n",
    "cns.consistency_plot()"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Aucun(e)",
  "hide_input": false,
  "kernelspec": {
   "display_name": "shapash39",
   "language": "python",
   "name": "shapash39"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}