{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Autism"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Autism, also known as Autism Spectrum Disorder (ASD), is a neurodevelopmental condition characterized by challenges in social interaction, communication, and repetitive behaviors. Individuals with autism may exhibit a wide range of abilities and symptoms, forming a spectrum. Understanding and accurately classifying autism can be a complex task due to the diversity within the spectrum. Machine Learning (ML) plays a vital role in addressing this challenge by leveraging algorithms to analyze patterns and make predictions based on data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data\n",
    "\n",
    "ID - ID of the patient\n",
    "\n",
    "A1_Score to A10_Score - Score based on Autism Spectrum Quotient (AQ) 10 item screening tool\n",
    "\n",
    "age - Age of the patient in years\n",
    "\n",
    "gender - Gender of the patient\n",
    "\n",
    "ethnicity - Ethnicity of the patient\n",
    "\n",
    "jaundice - Whether the patient had jaundice at the time of birth\n",
    "\n",
    "autism - Whether an immediate family member has been diagnosed with autism\n",
    "\n",
    "contry_of_res - Country of residence of the patient\n",
    "\n",
    "used_app_before - Whether the patient has undergone a screening test before\n",
    "\n",
    "result - Score for AQ1-10 screening test\n",
    "\n",
    "age_desc - Age of the patient\n",
    "\n",
    "relation - Relation of patient who completed the test\n",
    "\n",
    "Class/ASD - Classified result as 0 or 1. Here 0 represents No and 1 represents Yes. This is the target column, and during submission submit the values as 0 or 1 only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import confusion_matrix, accuracy_score, classification_report\n",
    "from sklearn.linear_model import LogisticRegression \n",
    "import joblib\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv(\"data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>ID</th>\n",
       "      <th>gender</th>\n",
       "      <th>A1_Score</th>\n",
       "      <th>A2_Score</th>\n",
       "      <th>A3_Score</th>\n",
       "      <th>A4_Score</th>\n",
       "      <th>A5_Score</th>\n",
       "      <th>A6_Score</th>\n",
       "      <th>A7_Score</th>\n",
       "      <th>A8_Score</th>\n",
       "      <th>...</th>\n",
       "      <th>jaundice</th>\n",
       "      <th>austim</th>\n",
       "      <th>age</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>contry_of_res</th>\n",
       "      <th>used_app_before</th>\n",
       "      <th>result</th>\n",
       "      <th>relation</th>\n",
       "      <th>age_desc</th>\n",
       "      <th>Class/ASD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>18.605397</td>\n",
       "      <td>White-European</td>\n",
       "      <td>United States</td>\n",
       "      <td>no</td>\n",
       "      <td>7.819715</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>13.829369</td>\n",
       "      <td>South Asian</td>\n",
       "      <td>Australia</td>\n",
       "      <td>no</td>\n",
       "      <td>10.544296</td>\n",
       "      <td>?</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>14.679893</td>\n",
       "      <td>White-European</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>no</td>\n",
       "      <td>13.167506</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>f</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>61.035288</td>\n",
       "      <td>South Asian</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>no</td>\n",
       "      <td>1.530098</td>\n",
       "      <td>?</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>m</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>14.256686</td>\n",
       "      <td>Black</td>\n",
       "      <td>Italy</td>\n",
       "      <td>no</td>\n",
       "      <td>7.949723</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>795</th>\n",
       "      <td>796</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>42.084907</td>\n",
       "      <td>White-European</td>\n",
       "      <td>United States</td>\n",
       "      <td>no</td>\n",
       "      <td>13.390868</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>797</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>17.669291</td>\n",
       "      <td>Asian</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>no</td>\n",
       "      <td>9.454201</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>798</td>\n",
       "      <td>m</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>18.242557</td>\n",
       "      <td>White-European</td>\n",
       "      <td>Jordan</td>\n",
       "      <td>no</td>\n",
       "      <td>6.805509</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>799</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>19.241473</td>\n",
       "      <td>Middle Eastern</td>\n",
       "      <td>United States</td>\n",
       "      <td>no</td>\n",
       "      <td>3.682732</td>\n",
       "      <td>Relative</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>800</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>32.170098</td>\n",
       "      <td>Asian</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>no</td>\n",
       "      <td>12.060168</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>800 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID gender  A1_Score  A2_Score  A3_Score  A4_Score  A5_Score  A6_Score  \\\n",
       "0      1      f         1         0         1         1         1         1   \n",
       "1      2      f         0         0         0         0         0         0   \n",
       "2      3      f         1         1         1         1         1         1   \n",
       "3      4      f         0         0         0         1         0         0   \n",
       "4      5      m         0         0         0         0         1         0   \n",
       "..   ...    ...       ...       ...       ...       ...       ...       ...   \n",
       "795  796      f         1         1         1         1         1         1   \n",
       "796  797      f         1         1         0         0         1         0   \n",
       "797  798      m         0         0         0         0         0         0   \n",
       "798  799      f         1         1         1         1         1         1   \n",
       "799  800      f         1         0         0         1         1         0   \n",
       "\n",
       "     A7_Score  A8_Score  ...  jaundice  austim        age        ethnicity  \\\n",
       "0           0         1  ...        no      no  18.605397   White-European   \n",
       "1           0         0  ...        no      no  13.829369      South Asian   \n",
       "2           0         0  ...        no      no  14.679893   White-European   \n",
       "3           0         0  ...        no      no  61.035288      South Asian   \n",
       "4           0         0  ...        no     yes  14.256686            Black   \n",
       "..        ...       ...  ...       ...     ...        ...              ...   \n",
       "795         1         1  ...        no     yes  42.084907   White-European   \n",
       "796         0         0  ...        no      no  17.669291            Asian   \n",
       "797         1         0  ...       yes      no  18.242557   White-European   \n",
       "798         0         1  ...        no     yes  19.241473  Middle Eastern    \n",
       "799         0         1  ...        no      no  32.170098            Asian   \n",
       "\n",
       "      contry_of_res used_app_before     result  relation     age_desc  \\\n",
       "0     United States              no   7.819715      Self  18 and more   \n",
       "1         Australia              no  10.544296         ?  18 and more   \n",
       "2    United Kingdom              no  13.167506      Self  18 and more   \n",
       "3       New Zealand              no   1.530098         ?  18 and more   \n",
       "4             Italy              no   7.949723      Self  18 and more   \n",
       "..              ...             ...        ...       ...          ...   \n",
       "795   United States              no  13.390868      Self  18 and more   \n",
       "796     New Zealand              no   9.454201      Self  18 and more   \n",
       "797          Jordan              no   6.805509      Self  18 and more   \n",
       "798   United States              no   3.682732  Relative  18 and more   \n",
       "799     New Zealand              no  12.060168      Self  18 and more   \n",
       "\n",
       "    Class/ASD  \n",
       "0           0  \n",
       "1           0  \n",
       "2           1  \n",
       "3           0  \n",
       "4           0  \n",
       "..        ...  \n",
       "795         1  \n",
       "796         0  \n",
       "797         1  \n",
       "798         0  \n",
       "799         0  \n",
       "\n",
       "[800 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>ID</th>\n",
       "      <th>A1_Score</th>\n",
       "      <th>A2_Score</th>\n",
       "      <th>A3_Score</th>\n",
       "      <th>A4_Score</th>\n",
       "      <th>A5_Score</th>\n",
       "      <th>A6_Score</th>\n",
       "      <th>A7_Score</th>\n",
       "      <th>A8_Score</th>\n",
       "      <th>A9_Score</th>\n",
       "      <th>A10_Score</th>\n",
       "      <th>age</th>\n",
       "      <th>result</th>\n",
       "      <th>Class/ASD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>800.0000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.00000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.00000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.00000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>400.5000</td>\n",
       "      <td>0.582500</td>\n",
       "      <td>0.28625</td>\n",
       "      <td>0.321250</td>\n",
       "      <td>0.41500</td>\n",
       "      <td>0.457500</td>\n",
       "      <td>0.20875</td>\n",
       "      <td>0.273750</td>\n",
       "      <td>0.717500</td>\n",
       "      <td>0.316250</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>28.612306</td>\n",
       "      <td>7.058530</td>\n",
       "      <td>0.231250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>231.0844</td>\n",
       "      <td>0.493455</td>\n",
       "      <td>0.45229</td>\n",
       "      <td>0.467249</td>\n",
       "      <td>0.49303</td>\n",
       "      <td>0.498502</td>\n",
       "      <td>0.40667</td>\n",
       "      <td>0.446161</td>\n",
       "      <td>0.450497</td>\n",
       "      <td>0.465303</td>\n",
       "      <td>0.498709</td>\n",
       "      <td>12.872373</td>\n",
       "      <td>3.788969</td>\n",
       "      <td>0.421896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.560505</td>\n",
       "      <td>-2.594654</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>200.7500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>19.282082</td>\n",
       "      <td>4.527556</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>400.5000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.479960</td>\n",
       "      <td>6.893472</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>600.2500</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>33.154755</td>\n",
       "      <td>9.892981</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>800.0000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.402488</td>\n",
       "      <td>13.390868</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID    A1_Score   A2_Score    A3_Score   A4_Score    A5_Score  \\\n",
       "count  800.0000  800.000000  800.00000  800.000000  800.00000  800.000000   \n",
       "mean   400.5000    0.582500    0.28625    0.321250    0.41500    0.457500   \n",
       "std    231.0844    0.493455    0.45229    0.467249    0.49303    0.498502   \n",
       "min      1.0000    0.000000    0.00000    0.000000    0.00000    0.000000   \n",
       "25%    200.7500    0.000000    0.00000    0.000000    0.00000    0.000000   \n",
       "50%    400.5000    1.000000    0.00000    0.000000    0.00000    0.000000   \n",
       "75%    600.2500    1.000000    1.00000    1.000000    1.00000    1.000000   \n",
       "max    800.0000    1.000000    1.00000    1.000000    1.00000    1.000000   \n",
       "\n",
       "        A6_Score    A7_Score    A8_Score    A9_Score   A10_Score         age  \\\n",
       "count  800.00000  800.000000  800.000000  800.000000  800.000000  800.000000   \n",
       "mean     0.20875    0.273750    0.717500    0.316250    0.460000   28.612306   \n",
       "std      0.40667    0.446161    0.450497    0.465303    0.498709   12.872373   \n",
       "min      0.00000    0.000000    0.000000    0.000000    0.000000    9.560505   \n",
       "25%      0.00000    0.000000    0.000000    0.000000    0.000000   19.282082   \n",
       "50%      0.00000    0.000000    1.000000    0.000000    0.000000   25.479960   \n",
       "75%      0.00000    1.000000    1.000000    1.000000    1.000000   33.154755   \n",
       "max      1.00000    1.000000    1.000000    1.000000    1.000000   72.402488   \n",
       "\n",
       "           result   Class/ASD  \n",
       "count  800.000000  800.000000  \n",
       "mean     7.058530    0.231250  \n",
       "std      3.788969    0.421896  \n",
       "min     -2.594654    0.000000  \n",
       "25%      4.527556    0.000000  \n",
       "50%      6.893472    0.000000  \n",
       "75%      9.892981    0.000000  \n",
       "max     13.390868    1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                 0\n",
       "gender             0\n",
       "A1_Score           0\n",
       "A2_Score           0\n",
       "A3_Score           0\n",
       "A4_Score           0\n",
       "A5_Score           0\n",
       "A6_Score           0\n",
       "A7_Score           0\n",
       "A8_Score           0\n",
       "A9_Score           0\n",
       "A10_Score          0\n",
       "jaundice           0\n",
       "austim             0\n",
       "age                0\n",
       "ethnicity          0\n",
       "contry_of_res      0\n",
       "used_app_before    0\n",
       "result             0\n",
       "relation           0\n",
       "age_desc           0\n",
       "Class/ASD          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.Data dosen't have a null value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.Data Encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>ID</th>\n",
       "      <th>gender</th>\n",
       "      <th>A1_Score</th>\n",
       "      <th>A2_Score</th>\n",
       "      <th>A3_Score</th>\n",
       "      <th>A4_Score</th>\n",
       "      <th>A5_Score</th>\n",
       "      <th>A6_Score</th>\n",
       "      <th>A7_Score</th>\n",
       "      <th>A8_Score</th>\n",
       "      <th>...</th>\n",
       "      <th>jaundice</th>\n",
       "      <th>austim</th>\n",
       "      <th>age</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>contry_of_res</th>\n",
       "      <th>used_app_before</th>\n",
       "      <th>result</th>\n",
       "      <th>relation</th>\n",
       "      <th>age_desc</th>\n",
       "      <th>Class/ASD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>18.605397</td>\n",
       "      <td>White-European</td>\n",
       "      <td>United States</td>\n",
       "      <td>no</td>\n",
       "      <td>7.819715</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>13.829369</td>\n",
       "      <td>South Asian</td>\n",
       "      <td>Australia</td>\n",
       "      <td>no</td>\n",
       "      <td>10.544296</td>\n",
       "      <td>?</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>14.679893</td>\n",
       "      <td>White-European</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>no</td>\n",
       "      <td>13.167506</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>f</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>61.035288</td>\n",
       "      <td>South Asian</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>no</td>\n",
       "      <td>1.530098</td>\n",
       "      <td>?</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>m</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>14.256686</td>\n",
       "      <td>Black</td>\n",
       "      <td>Italy</td>\n",
       "      <td>no</td>\n",
       "      <td>7.949723</td>\n",
       "      <td>Self</td>\n",
       "      <td>18 and more</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID gender  A1_Score  A2_Score  A3_Score  A4_Score  A5_Score  A6_Score  \\\n",
       "0   1      f         1         0         1         1         1         1   \n",
       "1   2      f         0         0         0         0         0         0   \n",
       "2   3      f         1         1         1         1         1         1   \n",
       "3   4      f         0         0         0         1         0         0   \n",
       "4   5      m         0         0         0         0         1         0   \n",
       "\n",
       "   A7_Score  A8_Score  ...  jaundice  austim        age       ethnicity  \\\n",
       "0         0         1  ...        no      no  18.605397  White-European   \n",
       "1         0         0  ...        no      no  13.829369     South Asian   \n",
       "2         0         0  ...        no      no  14.679893  White-European   \n",
       "3         0         0  ...        no      no  61.035288     South Asian   \n",
       "4         0         0  ...        no     yes  14.256686           Black   \n",
       "\n",
       "    contry_of_res used_app_before     result relation     age_desc Class/ASD  \n",
       "0   United States              no   7.819715     Self  18 and more         0  \n",
       "1       Australia              no  10.544296        ?  18 and more         0  \n",
       "2  United Kingdom              no  13.167506     Self  18 and more         1  \n",
       "3     New Zealand              no   1.530098        ?  18 and more         0  \n",
       "4           Italy              no   7.949723     Self  18 and more         0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat = {'ethnicity':'category',\n",
    "       'gender':'category', \n",
    "       'jaundice':'category',\n",
    "       'austim':'category',\n",
    "       'contry_of_res':'category', \n",
    "       'used_app_before':'category',\n",
    "        'age_desc':'category',\n",
    "        'relation':'category'}\n",
    "data = data.astype(cat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_columns = ['ethnicity', 'gender', 'jaundice', 'austim', 'contry_of_res', 'used_app_before', 'age_desc', 'relation']\n",
    "\n",
    "for col in cat_columns:\n",
    "    data[col] = data[col].cat.codes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>ID</th>\n",
       "      <th>gender</th>\n",
       "      <th>A1_Score</th>\n",
       "      <th>A2_Score</th>\n",
       "      <th>A3_Score</th>\n",
       "      <th>A4_Score</th>\n",
       "      <th>A5_Score</th>\n",
       "      <th>A6_Score</th>\n",
       "      <th>A7_Score</th>\n",
       "      <th>A8_Score</th>\n",
       "      <th>...</th>\n",
       "      <th>jaundice</th>\n",
       "      <th>austim</th>\n",
       "      <th>age</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>contry_of_res</th>\n",
       "      <th>used_app_before</th>\n",
       "      <th>result</th>\n",
       "      <th>relation</th>\n",
       "      <th>age_desc</th>\n",
       "      <th>Class/ASD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18.605397</td>\n",
       "      <td>10</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>7.819715</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.829369</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>10.544296</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.679893</td>\n",
       "      <td>10</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>13.167506</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>61.035288</td>\n",
       "      <td>8</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>1.530098</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14.256686</td>\n",
       "      <td>2</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>7.949723</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  gender  A1_Score  A2_Score  A3_Score  A4_Score  A5_Score  A6_Score  \\\n",
       "0   1       0         1         0         1         1         1         1   \n",
       "1   2       0         0         0         0         0         0         0   \n",
       "2   3       0         1         1         1         1         1         1   \n",
       "3   4       0         0         0         0         1         0         0   \n",
       "4   5       1         0         0         0         0         1         0   \n",
       "\n",
       "   A7_Score  A8_Score  ...  jaundice  austim        age  ethnicity  \\\n",
       "0         0         1  ...         0       0  18.605397         10   \n",
       "1         0         0  ...         0       0  13.829369          8   \n",
       "2         0         0  ...         0       0  14.679893         10   \n",
       "3         0         0  ...         0       0  61.035288          8   \n",
       "4         0         0  ...         0       1  14.256686          2   \n",
       "\n",
       "   contry_of_res  used_app_before     result  relation  age_desc  Class/ASD  \n",
       "0             58                0   7.819715         5         0          0  \n",
       "1              6                0  10.544296         0         0          0  \n",
       "2             57                0  13.167506         5         0          1  \n",
       "3             39                0   1.530098         0         0          0  \n",
       "4             32                0   7.949723         5         0          0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ID                   int64\n",
      "gender                int8\n",
      "A1_Score             int64\n",
      "A2_Score             int64\n",
      "A3_Score             int64\n",
      "A4_Score             int64\n",
      "A5_Score             int64\n",
      "A6_Score             int64\n",
      "A7_Score             int64\n",
      "A8_Score             int64\n",
      "A9_Score             int64\n",
      "A10_Score            int64\n",
      "jaundice              int8\n",
      "austim                int8\n",
      "age                float64\n",
      "ethnicity             int8\n",
      "contry_of_res         int8\n",
      "used_app_before       int8\n",
      "result             float64\n",
      "relation              int8\n",
      "age_desc              int8\n",
      "Class/ASD            int64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(data.dtypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.Drob unusiful data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data.drop('ID', axis=1)\n",
    "data=data.drop('used_app_before', axis=1)\n",
    "data=data.drop('relation', axis=1)\n",
    "data=data.drop('result', axis=1)\n",
    "data=data.drop('age_desc', axis=1)\n",
    "data=data.drop('contry_of_res', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.Split Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.drop('Class/ASD', axis=1)\n",
    "y = data['Class/ASD']\n",
    "X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2, random_state=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.Standard Scaler\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "X_train = scaler.fit_transform(X_train)\n",
    "X_val = scaler.transform(X_val)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LogisticRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>LogisticRegression()</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;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model.predict(X_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9\n"
     ]
    }
   ],
   "source": [
    "accuracy = accuracy_score(y_val, y_pred)\n",
    "print(\"Accuracy:\", accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>gender</th>\n",
       "      <th>A1_Score</th>\n",
       "      <th>A2_Score</th>\n",
       "      <th>A3_Score</th>\n",
       "      <th>A4_Score</th>\n",
       "      <th>A5_Score</th>\n",
       "      <th>A6_Score</th>\n",
       "      <th>A7_Score</th>\n",
       "      <th>A8_Score</th>\n",
       "      <th>A9_Score</th>\n",
       "      <th>A10_Score</th>\n",
       "      <th>jaundice</th>\n",
       "      <th>austim</th>\n",
       "      <th>age</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>Class/ASD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18.605397</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.829369</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.679893</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>61.035288</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>14.256686</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>795</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>42.084907</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17.669291</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>18.242557</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>19.241473</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32.170098</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>800 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     gender  A1_Score  A2_Score  A3_Score  A4_Score  A5_Score  A6_Score  \\\n",
       "0         0         1         0         1         1         1         1   \n",
       "1         0         0         0         0         0         0         0   \n",
       "2         0         1         1         1         1         1         1   \n",
       "3         0         0         0         0         1         0         0   \n",
       "4         1         0         0         0         0         1         0   \n",
       "..      ...       ...       ...       ...       ...       ...       ...   \n",
       "795       0         1         1         1         1         1         1   \n",
       "796       0         1         1         0         0         1         0   \n",
       "797       1         0         0         0         0         0         0   \n",
       "798       0         1         1         1         1         1         1   \n",
       "799       0         1         0         0         1         1         0   \n",
       "\n",
       "     A7_Score  A8_Score  A9_Score  A10_Score  jaundice  austim        age  \\\n",
       "0           0         1         1          1         0       0  18.605397   \n",
       "1           0         0         0          1         0       0  13.829369   \n",
       "2           0         0         1          1         0       0  14.679893   \n",
       "3           0         0         0          0         0       0  61.035288   \n",
       "4           0         0         1          1         0       1  14.256686   \n",
       "..        ...       ...       ...        ...       ...     ...        ...   \n",
       "795         1         1         1          1         0       1  42.084907   \n",
       "796         0         0         1          1         0       0  17.669291   \n",
       "797         1         0         1          1         1       0  18.242557   \n",
       "798         0         1         1          1         0       1  19.241473   \n",
       "799         0         1         1          1         0       0  32.170098   \n",
       "\n",
       "     ethnicity  Class/ASD  \n",
       "0           10          0  \n",
       "1            8          0  \n",
       "2           10          1  \n",
       "3            8          0  \n",
       "4            2          0  \n",
       "..         ...        ...  \n",
       "795         10          1  \n",
       "796          1          0  \n",
       "797         10          1  \n",
       "798          5          0  \n",
       "799          1          0  \n",
       "\n",
       "[800 rows x 16 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0]\n"
     ]
    }
   ],
   "source": [
    "input_data = np.array([1\t,0\t,0\t,0\t,0\t,0\t,0\t,1\t,0\t,1\t,1\t,1\t,0\t,18.242557\t,10])\n",
    "input_data_reshaped = input_data.reshape(1, -1)\n",
    "predication = model.predict(input_data_reshaped)\n",
    "print(predication)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save the model and the scaler\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['scaler.pkl']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joblib.dump(model, 'autism_model.pkl')\n",
    "joblib.dump(scaler, 'scaler.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import joblib\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = joblib.load(\"autism_model.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_input ={\n",
    "    \"A1_Score\": 1,\n",
    "  \"A2_Score\": 0,\n",
    "  \"A3_Score\": 0,\n",
    "  \"A4_Score\": 0,\n",
    "  \"A5_Score\": 0,\n",
    "  \"A6_Score\": 0,\n",
    "  \"A7_Score\": 0,\n",
    "  \"A8_Score\": 1,\n",
    "  \"A9_Score\": 0,\n",
    "  \"A10_Score\": 1,\n",
    "  \"jaundice\": 1,\n",
    "  \"autism\": 1,\n",
    "  \"age\": 18.242557,\n",
    "  \"gender\": 1,\n",
    "  \"ethnicity\":1\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1.        0.        0.        0.        0.        0.        0.\n",
      "   1.        0.        1.        1.        1.       18.242557  1.\n",
      "   1.      ]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Given dictionary\n",
    "data = {\n",
    "    'A1_Score': 1, 'A2_Score': 0, 'A3_Score': 0, 'A4_Score': 0, 'A5_Score': 0, \n",
    "    'A6_Score': 0, 'A7_Score': 0, 'A8_Score': 1, 'A9_Score': 0, 'A10_Score': 1, \n",
    "    'jaundice': 1, 'autism': 1, 'age': 18.242557, \"gender\": 1,\n",
    "  \"ethnicity\":1\n",
    "}\n",
    "\n",
    "# Convert the dictionary values to a list\n",
    "data_list = list(data.values())\n",
    "\n",
    "# Convert the list to a 2D numpy array\n",
    "data_array = np.array(data_list).reshape(1, -1)\n",
    "\n",
    "print(data_array)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(data_array)[0]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}