{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dd718ff4-36a5-4b2a-bbc6-9bfedec774e3",
   "metadata": {},
   "source": [
    "### US Automobile Accidents"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "822004fb-6aae-4266-a2e3-3fdf20a86cb3",
   "metadata": {},
   "source": [
    "#### Neural Network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "875de1c6-c8a1-4bff-b488-a17fbe0b8472",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "import matplotlib.pylab as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "57bb92a1-f6cd-458a-87c9-5d5f330474e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ALCHL_I</th>\n",
       "      <th>PROFIL_I_R</th>\n",
       "      <th>SUR_COND</th>\n",
       "      <th>VEH_INVL</th>\n",
       "      <th>MAX_SEV_IR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ALCHL_I  PROFIL_I_R  SUR_COND  VEH_INVL  MAX_SEV_IR\n",
       "0        2           0         1         1           0\n",
       "1        2           1         1         1           2\n",
       "2        1           0         1         1           0\n",
       "3        2           0         2         2           1\n",
       "4        2           1         1         2           1"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(r'/Users/patriciaxufre/Documents/SBE - Disciplinas/2957 | ABA/2024-25/Datasets Examples/accidentsnn.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "45f7f1ae-3663-4429-8711-e325c6729833",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['ALCHL_I'] = df['ALCHL_I'].replace({2: 0})\n",
    "df.SUR_COND = df.SUR_COND.astype('category')\n",
    "df.MAX_SEV_IR = df.MAX_SEV_IR.astype('category')\n",
    "processed = pd.get_dummies(df, columns = ['SUR_COND'])\n",
    "processed = processed.drop(columns = ['SUR_COND_9'])\n",
    "outcome = 'MAX_SEV_IR'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6c2642c4-c0e6-4d41-bb86-3204b6af632a",
   "metadata": {},
   "outputs": [],
   "source": [
    "predictors = [c for c in processed.columns if c != outcome]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d01d0e31-fdc2-4643-ad8c-4e0ad649ca43",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = processed[predictors]\n",
    "y = processed[outcome]\n",
    "train_X, valid_X, train_y, valid_y = train_test_split(X, y, test_size = 0.4, random_state = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "100e276d-be61-4a98-9014-e99cbf9c29c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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",
       "  --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-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>MLPClassifier(activation=&#x27;logistic&#x27;, hidden_layer_sizes=2, random_state=1,\n",
       "              solver=&#x27;lbfgs&#x27;)</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\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;MLPClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.neural_network.MLPClassifier.html\">?<span>Documentation for MLPClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>MLPClassifier(activation=&#x27;logistic&#x27;, hidden_layer_sizes=2, random_state=1,\n",
       "              solver=&#x27;lbfgs&#x27;)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "MLPClassifier(activation='logistic', hidden_layer_sizes=2, random_state=1,\n",
       "              solver='lbfgs')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = MLPClassifier(hidden_layer_sizes = (2), activation = 'logistic', solver = 'lbfgs', random_state = 1)\n",
    "clf.fit(train_X, train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "164081da-f17a-420b-9897-d563debd8a9d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.92      1.00      0.96       332\n",
      "           1       0.79      1.00      0.88       180\n",
      "           2       0.89      0.09      0.17        87\n",
      "\n",
      "    accuracy                           0.87       599\n",
      "   macro avg       0.86      0.70      0.67       599\n",
      "weighted avg       0.87      0.87      0.82       599\n",
      "\n",
      "Validation Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.90      1.00      0.95       219\n",
      "           1       0.78      0.99      0.87       119\n",
      "           2       0.71      0.08      0.14        62\n",
      "\n",
      "    accuracy                           0.85       400\n",
      "   macro avg       0.80      0.69      0.65       400\n",
      "weighted avg       0.84      0.85      0.80       400\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay\n",
    "# Predictions\n",
    "train_pred = clf.predict(train_X)\n",
    "valid_pred = clf.predict(valid_X)\n",
    "\n",
    "# Classification reports\n",
    "print(\"Train Classification Report:\")\n",
    "print(classification_report(train_y, train_pred))\n",
    "\n",
    "print(\"Validation Classification Report:\")\n",
    "print(classification_report(valid_y, valid_pred))\n",
    "\n",
    "# Confusion matrix for validation\n",
    "conf_matrix = confusion_matrix(valid_y, valid_pred)\n",
    "disp = ConfusionMatrixDisplay(conf_matrix)\n",
    "disp.plot(cmap='Blues')\n",
    "plt.title(\"Validation Confusion Matrix\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1f0f8428-e1ee-42a1-8326-fc8154807e3a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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_=this.hoverGroup1.selectAll(\".neg-values\").data(l);_.enter().append(\"text\").attr(\"class\",\"neg-values\").merge(_).attr(\"x\",e.xmapScaled+5).attr(\"y\",(function(t){return 4+(t.negyTop+t.negyBottom)/2})).attr(\"text-anchor\",\"start\").attr(\"font-size\",12).attr(\"stroke\",\"#fff\").attr(\"fill\",\"#fff\").attr(\"stroke-width\",\"4\").attr(\"stroke-linejoin\",\"round\").attr(\"opacity\",1).text(g),_.exit().remove();var x=this.hoverGroup2.selectAll(\".neg-values\").data(l);x.enter().append(\"text\").attr(\"class\",\"neg-values\").merge(x).attr(\"x\",e.xmapScaled+5).attr(\"y\",(function(t){return 4+(t.negyTop+t.negyBottom)/2})).attr(\"text-anchor\",\"start\").attr(\"font-size\",12).attr(\"fill\",this.colors[1]).text(g),x.exit().remove()}}},{key:\"draw\",value:function(){var t=this;if(this.props.explanations&&0!==this.props.explanations.length){(0,Ut.each)(this.props.explanations,(function(t,n){return t.origInd=n}));var n,e={},r={},i={},o=qi(this.props.explanations);try{for(o.s();!(n=o.n()).done;){var u=n.value;for(var a in u.features)void 0===e[a]&&(e[a]=0,r[a]=0,i[a]=0),u.features[a].effect>0?e[a]+=u.features[a].effect:r[a]-=u.features[a].effect,null!==u.features[a].value&&void 0!==u.features[a].value&&(i[a]+=1)}}catch(t){o.e(t)}finally{o.f()}this.usedFeatures=(0,Ut.sortBy)((0,Ut.keys)(e),(function(t){return-(e[t]+r[t])})),console.log(\"found \",this.usedFeatures.length,\" used features\"),this.posOrderedFeatures=(0,Ut.sortBy)(this.usedFeatures,(function(t){return e[t]})),this.negOrderedFeatures=(0,Ut.sortBy)(this.usedFeatures,(function(t){return-r[t]})),this.singleValueFeatures=(0,Ut.filter)(this.usedFeatures,(function(t){return i[t]>0}));var c=[\"sample order by similarity\",\"sample order by output value\",\"original sample ordering\"].concat(this.singleValueFeatures.map((function(n){return t.props.featureNames[n]})));null!=this.props.ordering_keys&&c.unshift(\"sample order by key\");var s=this.xlabel.selectAll(\"option\").data(c);s.enter().append(\"option\").merge(s).attr(\"value\",(function(t){return t})).text((function(t){return t})),s.exit().remove();var f=this.props.outNames[0]?this.props.outNames[0]:\"model output value\";(c=(0,Ut.map)(this.usedFeatures,(function(n){return[t.props.featureNames[n],t.props.featureNames[n]+\" effects\"]}))).unshift([\"model output value\",f]);var l=this.ylabel.selectAll(\"option\").data(c);l.enter().append(\"option\").merge(l).attr(\"value\",(function(t){return t[0]})).text((function(t){return t[1]})),l.exit().remove(),this.ylabel.style(\"top\",(this.height-10-this.topOffset)/2+this.topOffset+\"px\").style(\"left\",10-this.ylabel.node().offsetWidth/2+\"px\"),this.internalDraw()}}},{key:\"internalDraw\",value:function(){var t,n,e=this,r=qi(this.props.explanations);try{for(r.s();!(t=r.n()).done;){var i,o=t.value,u=qi(this.usedFeatures);try{for(u.s();!(i=u.n()).done;){var a=i.value;o.features.hasOwnProperty(a)||(o.features[a]={effect:0,value:0}),o.features[a].ind=a}}catch(t){u.e(t)}finally{u.f()}}}catch(t){r.e(t)}finally{r.f()}var c=this.xlabel.node().value,s=\"sample order by key\"===c&&null!=this.props.ordering_keys_time_format;if(this.xscale=s?Yi():Lt(),this.xaxis.scale(this.xscale),\"sample order by similarity\"===c)n=(0,Ut.sortBy)(this.props.explanations,(function(t){return t.simIndex})),(0,Ut.each)(n,(function(t,n){return t.xmap=n}));else if(\"sample order by output value\"===c)n=(0,Ut.sortBy)(this.props.explanations,(function(t){return-t.outValue})),(0,Ut.each)(n,(function(t,n){return t.xmap=n}));else if(\"original sample ordering\"===c)n=(0,Ut.sortBy)(this.props.explanations,(function(t){return t.origInd})),(0,Ut.each)(n,(function(t,n){return t.xmap=n}));else if(\"sample order by key\"===c)n=this.props.explanations,s?(0,Ut.each)(n,(function(t,n){return t.xmap=e.parseTime(e.props.ordering_keys[n])})):(0,Ut.each)(n,(function(t,n){return t.xmap=e.props.ordering_keys[n]})),n=(0,Ut.sortBy)(n,(function(t){return t.xmap}));else{var f=(0,Ut.findKey)(this.props.featureNames,(function(t){return t===c}));(0,Ut.each)(this.props.explanations,(function(t,n){return t.xmap=t.features[f].value}));var l=(0,Ut.sortBy)(this.props.explanations,(function(t){return t.xmap})),h=(0,Ut.map)(l,(function(t){return t.xmap}));if(\"string\"==typeof h[0])return void alert(\"Ordering by category names is not yet supported.\");var p,v,d=(0,Ut.min)(h),g=((0,Ut.max)(h)-d)/100;n=[];for(var y=0;y<l.length;++y){var m=l[y];if(p&&!v&&m.xmap-p.xmap<=g||v&&m.xmap-v.xmap<=g){v||((v=(0,Ut.cloneDeep)(p)).count=1);var _,x=qi(this.usedFeatures);try{for(x.s();!(_=x.n()).done;){var b=_.value;v.features[b].effect+=m.features[b].effect,v.features[b].value+=m.features[b].value}}catch(t){x.e(t)}finally{x.f()}v.count+=1}else if(p)if(v){var w,k=qi(this.usedFeatures);try{for(k.s();!(w=k.n()).done;){var S=w.value;v.features[S].effect/=v.count,v.features[S].value/=v.count}}catch(t){k.e(t)}finally{k.f()}n.push(v),v=void 0}else n.push(p);p=m}p.xmap-n[n.length-1].xmap>g&&n.push(p)}this.currUsedFeatures=this.usedFeatures,this.currPosOrderedFeatures=this.posOrderedFeatures,this.currNegOrderedFeatures=this.negOrderedFeatures;var M=this.ylabel.node().value;if(\"model output value\"!==M){var A=n;n=(0,Ut.cloneDeep)(n);for(var T=(0,Ut.findKey)(this.props.featureNames,(function(t){return t===M})),O=0;O<n.length;++O){var j=n[O].features[T];n[O].features={},n[O].features[T]=j,A[O].remapped_version=n[O]}this.currUsedFeatures=[T],this.currPosOrderedFeatures=[T],this.currNegOrderedFeatures=[T]}this.currExplanations=n,\"identity\"===this.props.link?this.invLinkFunction=function(t){return e.props.baseValue+t}:\"logit\"===this.props.link?this.invLinkFunction=function(t){return 1/(1+Math.exp(-(e.props.baseValue+t)))}:console.log(\"ERROR: Unrecognized link function: 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t.effect<0})),(function(t){return-t.effect})))||0;N=Math.max(N,2.2*Math.max(U,R))}this.yscale.domain([-N/2,N/2]).range([this.height-10,this.topOffset]),this.yaxisElement.attr(\"transform\",\"translate(\"+this.leftOffset+\",0)\").call(this.yaxis);for(var P=0;P<F;++P){var z,I=n[P].features,B=-((0,Ut.sum)((0,Ut.map)((0,Ut.filter)(I,(function(t){return t.effect<0})),(function(t){return-t.effect})))||0),H=void 0,W=qi(this.currPosOrderedFeatures);try{for(W.s();!(z=W.n()).done;)I[H=z.value].posyTop=this.yscale(B),I[H].effect>0&&(B+=I[H].effect),I[H].posyBottom=this.yscale(B),I[H].ind=H}catch(t){W.e(t)}finally{W.f()}var V,Y=B,q=qi(this.currNegOrderedFeatures);try{for(q.s();!(V=q.n()).done;)I[H=V.value].negyTop=this.yscale(B),I[H].effect<0&&(B-=I[H].effect),I[H].negyBottom=this.yscale(B)}catch(t){q.e(t)}finally{q.f()}n[P].joinPoint=Y,n[P].joinPointy=this.yscale(Y)}var G=we().x((function(t){return t[0]})).y((function(t){return t[1]})),Z=this.mainGroup.selectAll(\".force-bar-array-area-pos\").data(this.currUsedFeatures);Z.enter().append(\"path\").attr(\"class\",\"force-bar-array-area-pos\").merge(Z).attr(\"d\",(function(t){var e=(0,Ut.map)((0,Ut.range)(F),(function(e){return[n[e].xmapScaled,n[e].features[t].posyTop]})),r=(0,Ut.map)((0,Ut.rangeRight)(F),(function(e){return[n[e].xmapScaled,n[e].features[t].posyBottom]}));return G(e.concat(r))})).attr(\"fill\",this.colors[0]),Z.exit().remove();var X=this.mainGroup.selectAll(\".force-bar-array-area-neg\").data(this.currUsedFeatures);X.enter().append(\"path\").attr(\"class\",\"force-bar-array-area-neg\").merge(X).attr(\"d\",(function(t){var e=(0,Ut.map)((0,Ut.range)(F),(function(e){return[n[e].xmapScaled,n[e].features[t].negyTop]})),r=(0,Ut.map)((0,Ut.rangeRight)(F),(function(e){return[n[e].xmapScaled,n[e].features[t].negyBottom]}));return G(e.concat(r))})).attr(\"fill\",this.colors[1]),X.exit().remove();var K=this.mainGroup.selectAll(\".force-bar-array-divider-pos\").data(this.currUsedFeatures);K.enter().append(\"path\").attr(\"class\",\"force-bar-array-divider-pos\").merge(K).attr(\"d\",(function(t){var e=(0,Ut.map)((0,Ut.range)(F),(function(e){return[n[e].xmapScaled,n[e].features[t].posyBottom]}));return G(e)})).attr(\"fill\",\"none\").attr(\"stroke-width\",1).attr(\"stroke\",(function(){return e.colors[0].brighter(1.2)})),K.exit().remove();var J=this.mainGroup.selectAll(\".force-bar-array-divider-neg\").data(this.currUsedFeatures);J.enter().append(\"path\").attr(\"class\",\"force-bar-array-divider-neg\").merge(J).attr(\"d\",(function(t){var e=(0,Ut.map)((0,Ut.range)(F),(function(e){return[n[e].xmapScaled,n[e].features[t].negyTop]}));return G(e)})).attr(\"fill\",\"none\").attr(\"stroke-width\",1).attr(\"stroke\",(function(){return e.colors[1].brighter(1.5)})),J.exit().remove();for(var Q=function(t,n,e,r,i){var o,u,a,c;\"pos\"===i?(o=t[e].features[n].posyBottom,u=t[e].features[n].posyTop):(o=t[e].features[n].negyBottom,u=t[e].features[n].negyTop);for(var s=e+1;s<=r;++s)\"pos\"===i?(a=t[s].features[n].posyBottom,c=t[s].features[n].posyTop):(a=t[s].features[n].negyBottom,c=t[s].features[n].negyTop),a>o&&(o=a),c<u&&(u=c);return{top:o,bottom:u}},tt=[],nt=0,et=[\"pos\",\"neg\"];nt<et.length;nt++){var rt,it=et[nt],ot=qi(this.currUsedFeatures);try{for(ot.s();!(rt=ot.n()).done;)for(var ut=rt.value,at=0,ct=0,st=0,ft={top:0,bottom:0},lt=void 0;ct<F-1;){for(;st<100&&ct<F-1;)++ct,st=n[ct].xmapScaled-n[at].xmapScaled;for(ft=Q(n,ut,at,ct,it);ft.bottom-ft.top<20&&at<ct;)++at,ft=Q(n,ut,at,ct,it);if(st=n[ct].xmapScaled-n[at].xmapScaled,ft.bottom-ft.top>=20&&st>=100){for(;ct<F-1;){if(++ct,!((lt=Q(n,ut,at,ct,it)).bottom-lt.top>20)){--ct;break}ft=lt}st=n[ct].xmapScaled-n[at].xmapScaled,tt.push([(n[ct].xmapScaled+n[at].xmapScaled)/2,(ft.top+ft.bottom)/2,this.props.featureNames[ut]]);var ht=n[ct].xmapScaled;for(at=ct;ht+100>n[at].xmapScaled&&at<F-1;)++at;ct=at}}}catch(t){ot.e(t)}finally{ot.f()}}var pt=this.onTopGroup.selectAll(\".force-bar-array-flabels\").data(tt);pt.enter().append(\"text\").attr(\"class\",\"force-bar-array-flabels\").merge(pt).attr(\"x\",(function(t){return t[0]})).attr(\"y\",(function(t){return t[1]+4})).text((function(t){return t[2]})),pt.exit().remove()}},{key:\"componentWillUnmount\",value:function(){window.removeEventListener(\"resize\",this.redraw)}},{key:\"render\",value:function(){var n=this;return t.createElement(\"div\",{ref:function(t){return n.wrapper=ne(t)},style:{textAlign:\"center\"}},t.createElement(\"style\",{dangerouslySetInnerHTML:{__html:\"\\n          .force-bar-array-wrapper {\\n            text-align: center;\\n          }\\n          .force-bar-array-xaxis path {\\n            fill: none;\\n            opacity: 0.4;\\n          }\\n          .force-bar-array-xaxis .domain {\\n            opacity: 0;\\n          }\\n          .force-bar-array-xaxis paths {\\n            display: none;\\n          }\\n          .force-bar-array-yaxis path {\\n            fill: none;\\n            opacity: 0.4;\\n          }\\n          .force-bar-array-yaxis paths {\\n            display: none;\\n          }\\n          .tick line {\\n            stroke: #000;\\n            stroke-width: 1px;\\n            opacity: 0.4;\\n          }\\n          .tick text {\\n            fill: #000;\\n            opacity: 0.5;\\n            font-size: 12px;\\n            padding: 0px;\\n          }\\n          .force-bar-array-flabels {\\n            font-size: 12px;\\n            fill: #fff;\\n            text-anchor: middle;\\n          }\\n          .additive-force-array-xlabel {\\n            background: none;\\n            border: 1px solid #ccc;\\n            opacity: 0.5;\\n            margin-bottom: 0px;\\n            font-size: 12px;\\n            font-family: arial;\\n            margin-left: 80px;\\n            max-width: 300px;\\n          }\\n          .additive-force-array-xlabel:focus {\\n            outline: none;\\n          }\\n          .additive-force-array-ylabel {\\n            position: relative;\\n            top: 0px;\\n            left: 0px;\\n            transform: rotate(-90deg);\\n            background: none;\\n            border: 1px solid #ccc;\\n            opacity: 0.5;\\n            margin-bottom: 0px;\\n            font-size: 12px;\\n            font-family: arial;\\n            max-width: 150px;\\n          }\\n          .additive-force-array-ylabel:focus {\\n            outline: none;\\n          }\\n          .additive-force-array-hoverLine {\\n            stroke-width: 1px;\\n            stroke: #fff;\\n            opacity: 1;\\n          }\"}}),t.createElement(\"select\",{className:\"additive-force-array-xlabel\"}),t.createElement(\"div\",{style:{height:\"0px\",textAlign:\"left\"}},t.createElement(\"select\",{className:\"additive-force-array-ylabel\"})),t.createElement(\"svg\",{ref:function(t){return n.svg=ne(t)},style:{userSelect:\"none\",display:\"block\",fontFamily:\"arial\",sansSerif:!0}}))}}],i&&Xi(r.prototype,i),Object.defineProperty(r,\"prototype\",{writable:!1}),r;var r,i}(t.Component);no.defaultProps={plot_cmap:\"RdBu\",ordering_keys:null,ordering_keys_time_format:null};const eo=no;window.SHAP={SimpleListVisualizer:Yt,AdditiveForceVisualizer:Ee,AdditiveForceArrayVisualizer:eo,React:t,ReactDom:n}})()})();\n",
       "</script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import shap\n",
    "shap.initjs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c14bc022-2292-49ea-8360-1f71bf1d3169",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using 599 background data samples could cause slower run times. Consider using shap.sample(data, K) or shap.kmeans(data, K) to summarize the background as K samples.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "33b8514ebdee43ab9a9707274155266b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/400 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(400, 7, 3)\n"
     ]
    }
   ],
   "source": [
    "explainer = shap.KernelExplainer(clf.predict_proba, train_X)\n",
    "shap_values = explainer(valid_X)\n",
    "print(np.shape(shap_values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f77c1a71-6c2e-46b6-97b5-fc57798e7802",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5.07069712e-15, 5.76598616e-01, 4.23401384e-01])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict_proba(valid_X)[0] # first observation of the validation set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b808c16f-6022-4e8c-a931-361161d2d714",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# waterfall plot for class 0\n",
    "shap.plots.waterfall(shap_values[0,:,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5259089-5e36-4b99-b5ae-15891ebfd096",
   "metadata": {},
   "source": [
    "#### The fact that the road was wet at the time of the accident, decreases the predicted probability of belonging to the 'no injuries' class by 0.33."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b255fc9f-24aa-4687-81a2-87dc7b926bc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# waterfall plot for class 1\n",
    "shap.plots.waterfall(shap_values[0,:,1])\n",
    "# waterfall plot for class 2\n",
    "shap.plots.waterfall(shap_values[0,:,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b8e002ff-fdf2-4cc0-ab07-bd6642a17f76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x33fb6b7d0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate the mean SHAPLEY VALUES for each class\n",
    "mean_0 = np.mean(np.abs(shap_values.values[:,:,0]), axis = 0)\n",
    "mean_1 = np.mean(np.abs(shap_values.values[:,:,1]), axis = 0)\n",
    "mean_2 = np.mean(np.abs(shap_values.values[:,:,2]), axis = 0)\n",
    "\n",
    "df = pd.DataFrame({'no injuries': mean_0, 'injury': mean_1, 'fatality': mean_2})\n",
    "\n",
    "#plot mean SHAPLEY VALUES\n",
    "fig, ax = plt.subplots(1,1,figsize=(20,20))\n",
    "df.plot.bar(ax=ax)\n",
    "\n",
    "ax.set_ylabel('Mean SHAP', size = 30)\n",
    "ax.set_xticklabels(X.columns, rotation = 45, size=20)\n",
    "ax.legend(fontsize=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a3c91b9e-d702-4e53-8477-0beb8519ef07",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(400, 7)\n"
     ]
    }
   ],
   "source": [
    "# get model predictions\n",
    "preds = clf.predict(valid_X)\n",
    "new_shap_values = []\n",
    "for i, pred in enumerate(preds):\n",
    "    # get shap values for predicted class\n",
    "    new_shap_values.append(shap_values.values[i][:,pred])\n",
    "shap_values.values = np.array(new_shap_values)\n",
    "print(shap_values.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4eb2554f-b6f6-4792-9bb2-c06cdc0064c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.plots.bar(shap_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "bf778d98-4abf-40ce-b50e-2978e708d539",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x430 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shap.plots.beeswarm(shap_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f77122d2-ae37-4c97-baad-242eae461e1f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:base] *",
   "language": "python",
   "name": "conda-base-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}