{
 "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": 3,
   "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": 5,
   "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": 6,
   "id": "6c2642c4-c0e6-4d41-bb86-3204b6af632a",
   "metadata": {},
   "outputs": [],
   "source": [
    "predictors = [c for c in processed.columns if c != outcome]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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": 8,
   "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": 8,
     "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": 9,
   "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": 10,
   "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": 28,
   "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": "4cdbd04158134ced8d958c1772e7a7a4",
       "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": [
    "e\n",
    "print(np.shape(shap_values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "f77c1a71-6c2e-46b6-97b5-fc57798e7802",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4.48098425e-13, 7.61360225e-01, 2.38639775e-01])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5259089-5e36-4b99-b5ae-15891ebfd096",
   "metadata": {},
   "source": [
    "#### The fact that the road is wet decreases the predicted probability of belonging to the 'no injuries' class by 0.48."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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[2,:,1])\n",
    "# waterfall plot for class 2\n",
    "shap.plots.waterfall(shap_values[2,:,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b8e002ff-fdf2-4cc0-ab07-bd6642a17f76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x338b8b380>"
      ]
     },
     "execution_count": 54,
     "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",
    "\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": 56,
   "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",
    "    \n",
    "shap_values.values = np.array(new_shap_values)\n",
    "print(shap_values.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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
}