script-Copy2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ac46269b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "506e121d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"Training.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a8f7b54a",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>itching</th>\n",
       "      <th>skin_rash</th>\n",
       "      <th>nodal_skin_eruptions</th>\n",
       "      <th>continuous_sneezing</th>\n",
       "      <th>shivering</th>\n",
       "      <th>chills</th>\n",
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       "      <th>stomach_pain</th>\n",
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       "      <th>...</th>\n",
       "      <th>scurring</th>\n",
       "      <th>skin_peeling</th>\n",
       "      <th>silver_like_dusting</th>\n",
       "      <th>small_dents_in_nails</th>\n",
       "      <th>inflammatory_nails</th>\n",
       "      <th>blister</th>\n",
       "      <th>red_sore_around_nose</th>\n",
       "      <th>yellow_crust_ooze</th>\n",
       "      <th>prognosis</th>\n",
       "      <th>Unnamed: 133</th>\n",
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       "      <td>Fungal infection</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 134 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   itching  skin_rash  nodal_skin_eruptions  continuous_sneezing  shivering  \\\n",
       "0        1          1                     1                    0          0   \n",
       "1        0          1                     1                    0          0   \n",
       "2        1          0                     1                    0          0   \n",
       "3        1          1                     0                    0          0   \n",
       "4        1          1                     1                    0          0   \n",
       "\n",
       "   chills  joint_pain  stomach_pain  acidity  ulcers_on_tongue  ...  scurring  \\\n",
       "0       0           0             0        0                 0  ...         0   \n",
       "1       0           0             0        0                 0  ...         0   \n",
       "2       0           0             0        0                 0  ...         0   \n",
       "3       0           0             0        0                 0  ...         0   \n",
       "4       0           0             0        0                 0  ...         0   \n",
       "\n",
       "   skin_peeling  silver_like_dusting  small_dents_in_nails  \\\n",
       "0             0                    0                     0   \n",
       "1             0                    0                     0   \n",
       "2             0                    0                     0   \n",
       "3             0                    0                     0   \n",
       "4             0                    0                     0   \n",
       "\n",
       "   inflammatory_nails  blister  red_sore_around_nose  yellow_crust_ooze  \\\n",
       "0                   0        0                     0                  0   \n",
       "1                   0        0                     0                  0   \n",
       "2                   0        0                     0                  0   \n",
       "3                   0        0                     0                  0   \n",
       "4                   0        0                     0                  0   \n",
       "\n",
       "          prognosis  Unnamed: 133  \n",
       "0  Fungal infection           NaN  \n",
       "1  Fungal infection           NaN  \n",
       "2  Fungal infection           NaN  \n",
       "3  Fungal infection           NaN  \n",
       "4  Fungal infection           NaN  \n",
       "\n",
       "[5 rows x 134 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "77025d88",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('Unnamed: 133',axis = 1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3e127ac7",
   "metadata": {},
   "outputs": [
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       "      <td>-0.033480</td>\n",
       "      <td>-0.023073</td>\n",
       "      <td>-0.067765</td>\n",
       "      <td>-0.061889</td>\n",
       "      <td>-0.033480</td>\n",
       "      <td>-0.033480</td>\n",
       "      <td>-0.023073</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023073</td>\n",
       "      <td>-0.023073</td>\n",
       "      <td>-0.023073</td>\n",
       "      <td>-0.023720</td>\n",
       "      <td>-0.023720</td>\n",
       "      <td>-0.023720</td>\n",
       "      <td>-0.023720</td>\n",
       "      <td>0.946120</td>\n",
       "      <td>0.946120</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>132 rows × 132 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       itching  skin_rash  nodal_skin_eruptions  \\\n",
       "itching               1.000000   0.318158              0.326439   \n",
       "skin_rash             0.318158   1.000000              0.298143   \n",
       "nodal_skin_eruptions  0.326439   0.298143              1.000000   \n",
       "continuous_sneezing  -0.086906  -0.094786             -0.032566   \n",
       "shivering            -0.059893  -0.065324             -0.022444   \n",
       "...                        ...        ...                   ...   \n",
       "small_dents_in_nails -0.061573   0.331087             -0.023073   \n",
       "inflammatory_nails   -0.061573   0.331087             -0.023073   \n",
       "blister              -0.061573   0.331087             -0.023073   \n",
       "red_sore_around_nose -0.061573   0.331087             -0.023073   \n",
       "yellow_crust_ooze    -0.061573   0.331087             -0.023073   \n",
       "\n",
       "                      continuous_sneezing  shivering    chills  joint_pain  \\\n",
       "itching                         -0.086906  -0.059893 -0.175905   -0.160650   \n",
       "skin_rash                       -0.094786  -0.065324 -0.029324    0.171134   \n",
       "nodal_skin_eruptions            -0.032566  -0.022444 -0.065917   -0.060200   \n",
       "continuous_sneezing              1.000000   0.608981  0.446238   -0.087351   \n",
       "shivering                        0.608981   1.000000  0.295332   -0.060200   \n",
       "...                                   ...        ...       ...         ...   \n",
       "small_dents_in_nails            -0.033480  -0.023073 -0.067765    0.359845   \n",
       "inflammatory_nails              -0.033480  -0.023073 -0.067765    0.359845   \n",
       "blister                         -0.033480  -0.023073 -0.067765   -0.061889   \n",
       "red_sore_around_nose            -0.033480  -0.023073 -0.067765   -0.061889   \n",
       "yellow_crust_ooze               -0.033480  -0.023073 -0.067765   -0.061889   \n",
       "\n",
       "                      stomach_pain   acidity  ulcers_on_tongue  ...  \\\n",
       "itching                   0.202850 -0.086906         -0.059893  ...   \n",
       "skin_rash                 0.161784 -0.094786         -0.065324  ...   \n",
       "nodal_skin_eruptions     -0.032566 -0.032566         -0.022444  ...   \n",
       "continuous_sneezing      -0.047254 -0.047254         -0.032566  ...   \n",
       "shivering                -0.032566 -0.032566         -0.022444  ...   \n",
       "...                            ...       ...               ...  ...   \n",
       "small_dents_in_nails     -0.033480 -0.033480         -0.023073  ...   \n",
       "inflammatory_nails       -0.033480 -0.033480         -0.023073  ...   \n",
       "blister                  -0.033480 -0.033480         -0.023073  ...   \n",
       "red_sore_around_nose     -0.033480 -0.033480         -0.023073  ...   \n",
       "yellow_crust_ooze        -0.033480 -0.033480         -0.023073  ...   \n",
       "\n",
       "                      pus_filled_pimples  blackheads  scurring  skin_peeling  \\\n",
       "itching                        -0.059893   -0.059893 -0.059893     -0.061573   \n",
       "skin_rash                       0.320859    0.320859  0.320859      0.331087   \n",
       "nodal_skin_eruptions           -0.022444   -0.022444 -0.022444     -0.023073   \n",
       "continuous_sneezing            -0.032566   -0.032566 -0.032566     -0.033480   \n",
       "shivering                      -0.022444   -0.022444 -0.022444     -0.023073   \n",
       "...                                  ...         ...       ...           ...   \n",
       "small_dents_in_nails           -0.023073   -0.023073 -0.023073      0.946120   \n",
       "inflammatory_nails             -0.023073   -0.023073 -0.023073      0.946120   \n",
       "blister                        -0.023073   -0.023073 -0.023073     -0.023720   \n",
       "red_sore_around_nose           -0.023073   -0.023073 -0.023073     -0.023720   \n",
       "yellow_crust_ooze              -0.023073   -0.023073 -0.023073     -0.023720   \n",
       "\n",
       "                      silver_like_dusting  small_dents_in_nails  \\\n",
       "itching                         -0.061573             -0.061573   \n",
       "skin_rash                        0.331087              0.331087   \n",
       "nodal_skin_eruptions            -0.023073             -0.023073   \n",
       "continuous_sneezing             -0.033480             -0.033480   \n",
       "shivering                       -0.023073             -0.023073   \n",
       "...                                   ...                   ...   \n",
       "small_dents_in_nails             0.946120              1.000000   \n",
       "inflammatory_nails               0.946120              0.946120   \n",
       "blister                         -0.023720             -0.023720   \n",
       "red_sore_around_nose            -0.023720             -0.023720   \n",
       "yellow_crust_ooze               -0.023720             -0.023720   \n",
       "\n",
       "                      inflammatory_nails   blister  red_sore_around_nose  \\\n",
       "itching                        -0.061573 -0.061573             -0.061573   \n",
       "skin_rash                       0.331087  0.331087              0.331087   \n",
       "nodal_skin_eruptions           -0.023073 -0.023073             -0.023073   \n",
       "continuous_sneezing            -0.033480 -0.033480             -0.033480   \n",
       "shivering                      -0.023073 -0.023073             -0.023073   \n",
       "...                                  ...       ...                   ...   \n",
       "small_dents_in_nails            0.946120 -0.023720             -0.023720   \n",
       "inflammatory_nails              1.000000 -0.023720             -0.023720   \n",
       "blister                        -0.023720  1.000000              0.946120   \n",
       "red_sore_around_nose           -0.023720  0.946120              1.000000   \n",
       "yellow_crust_ooze              -0.023720  0.946120              0.946120   \n",
       "\n",
       "                      yellow_crust_ooze  \n",
       "itching                       -0.061573  \n",
       "skin_rash                      0.331087  \n",
       "nodal_skin_eruptions          -0.023073  \n",
       "continuous_sneezing           -0.033480  \n",
       "shivering                     -0.023073  \n",
       "...                                 ...  \n",
       "small_dents_in_nails          -0.023720  \n",
       "inflammatory_nails            -0.023720  \n",
       "blister                        0.946120  \n",
       "red_sore_around_nose           0.946120  \n",
       "yellow_crust_ooze              1.000000  \n",
       "\n",
       "[132 rows x 132 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "34931acb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "itching                 0\n",
       "skin_rash               0\n",
       "nodal_skin_eruptions    0\n",
       "continuous_sneezing     0\n",
       "shivering               0\n",
       "                       ..\n",
       "inflammatory_nails      0\n",
       "blister                 0\n",
       "red_sore_around_nose    0\n",
       "yellow_crust_ooze       0\n",
       "prognosis               0\n",
       "Length: 133, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7cddf3e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=df.iloc[:,0:132]\n",
    "y=df.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "882d5f86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                              Fungal infection\n",
       "1                              Fungal infection\n",
       "2                              Fungal infection\n",
       "3                              Fungal infection\n",
       "4                              Fungal infection\n",
       "                         ...                   \n",
       "4915    (vertigo) Paroymsal  Positional Vertigo\n",
       "4916                                       Acne\n",
       "4917                    Urinary tract infection\n",
       "4918                                  Psoriasis\n",
       "4919                                   Impetigo\n",
       "Name: prognosis, Length: 4920, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6b3fc5fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Fungal infection', 'Allergy', 'GERD', 'Chronic cholestasis',\n",
       "       'Drug Reaction', 'Peptic ulcer diseae', 'AIDS', 'Diabetes ',\n",
       "       'Gastroenteritis', 'Bronchial Asthma', 'Hypertension ', 'Migraine',\n",
       "       'Cervical spondylosis', 'Paralysis (brain hemorrhage)', 'Jaundice',\n",
       "       'Malaria', 'Chicken pox', 'Dengue', 'Typhoid', 'hepatitis A',\n",
       "       'Hepatitis B', 'Hepatitis C', 'Hepatitis D', 'Hepatitis E',\n",
       "       'Alcoholic hepatitis', 'Tuberculosis', 'Common Cold', 'Pneumonia',\n",
       "       'Dimorphic hemmorhoids(piles)', 'Heart attack', 'Varicose veins',\n",
       "       'Hypothyroidism', 'Hyperthyroidism', 'Hypoglycemia',\n",
       "       'Osteoarthristis', 'Arthritis',\n",
       "       '(vertigo) Paroymsal  Positional Vertigo', 'Acne',\n",
       "       'Urinary tract infection', 'Psoriasis', 'Impetigo'], dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['prognosis'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "52627ad6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.36687321, 0.40145503, 0.11015398, 0.1768855 , 0.11424344,\n",
       "       0.4011593 , 0.37979759, 0.16221982, 0.166695  , 0.08812935,\n",
       "       0.11232591, 0.54767372, 0.15512269, 0.10150188, 0.58401606,\n",
       "       0.09612166, 0.09592127, 0.11696746, 0.17455757, 0.3056166 ,\n",
       "       0.20280115, 0.29231102, 0.09996373, 0.09419416, 0.3201459 ,\n",
       "       0.54156106, 0.08037814, 0.27657396, 0.38502123, 0.09509869,\n",
       "       0.16459759, 0.49608386, 0.43915221, 0.33233596, 0.49615426,\n",
       "       0.51530489, 0.1142471 , 0.16954725, 0.1756515 , 0.47973633,\n",
       "       0.33421728, 0.2399544 , 0.10956444, 0.4349072 , 0.09992988,\n",
       "       0.00163068, 0.12322532, 0.24915973, 0.3865898 , 0.24563497,\n",
       "       0.25924793, 0.1347044 , 0.10949353, 0.12433745, 0.1501673 ,\n",
       "       0.11789455, 0.37792712, 0.08329264, 0.18320238, 0.10900567,\n",
       "       0.10686971, 0.1071858 , 0.1026066 , 0.18040783, 0.24758684,\n",
       "       0.1037832 , 0.10521143, 0.16466015, 0.10405976, 0.0909799 ,\n",
       "       0.11233167, 0.12629366, 0.10836014, 0.11509922, 0.27929497,\n",
       "       0.09970889, 0.10610349, 0.12787955, 0.09693633, 0.1174765 ,\n",
       "       0.16802039, 0.17986146, 0.19345449, 0.11114386, 0.10573175,\n",
       "       0.26089864, 0.12475878, 0.11359853, 0.11448159, 0.11802683,\n",
       "       0.07346475, 0.11763477, 0.1060177 , 0.0906961 , 0.10157278,\n",
       "       0.18033779, 0.32860897, 0.31469674, 0.12552176, 0.2027649 ,\n",
       "       0.10044899, 0.18765087, 0.11547948, 0.09539998, 0.10833652,\n",
       "       0.09568468, 0.17972894, 0.11683405, 0.11324317, 0.10216041,\n",
       "       0.1030549 , 0.11745019, 0.10033197, 0.11986906, 0.11126141,\n",
       "       0.12886775, 0.1207178 , 0.095685  , 0.11306198, 0.10408621,\n",
       "       0.11157131, 0.16915054, 0.08406724, 0.09527911, 0.10097868,\n",
       "       0.10233026, 0.08840126, 0.10857468, 0.09870228, 0.09440886,\n",
       "       0.10123306, 0.10365121])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.feature_selection import mutual_info_classif\n",
    "mutual_info=mutual_info_classif(x, y)\n",
    "mutual_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "71ca1aa9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fatigue                0.584016\n",
       "vomiting               0.547674\n",
       "high_fever             0.541561\n",
       "loss_of_appetite       0.515305\n",
       "nausea                 0.496154\n",
       "                         ...   \n",
       "pus_filled_pimples     0.084067\n",
       "weakness_in_limbs      0.083293\n",
       "sunken_eyes            0.080378\n",
       "foul_smell_of urine    0.073465\n",
       "fluid_overload         0.001631\n",
       "Length: 132, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mutual_info=pd.Series(mutual_info)\n",
    "mutual_info.index=x.columns\n",
    "mutual_info.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "519fa3cf",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n",
      "Index: 132 entries, itching to yellow_crust_ooze\n",
      "Series name: None\n",
      "Non-Null Count  Dtype  \n",
      "--------------  -----  \n",
      "132 non-null    float64\n",
      "dtypes: float64(1)\n",
      "memory usage: 6.1+ KB\n"
     ]
    }
   ],
   "source": [
    "mutual_info.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e863004c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['nodal_skin_eruptions','continuous_sneezing','shivering','stomach_pain','acidity','ulcers_on_tongue','muscle_wasting',\n",
    "'burning_micturition','spotting_ urination','weight_gain','anxiety','cold_hands_and_feets','mood_swings',\n",
    "'restlessness','patches_in_throat','irregular_sugar_level','sunken_eyes',\n",
    "'sweating','dehydration','indigestion','pain_behind_the_eyes','back_pain','constipation','yellow_urine',\n",
    "'acute_liver_failure','fluid_overload','swelling_of_stomach','throat_irritation','redness_of_eyes','sinus_pressure','runny_nose','congestion',\n",
    "'weakness_in_limbs','fast_heart_rate','pain_during_bowel_movements','pain_in_anal_region','bloody_stool',\n",
    "'irritation_in_anus','neck_pain','cramps','bruising','obesity','swollen_legs','swollen_blood_vessels',\n",
    "'puffy_face_and_eyes','enlarged_thyroid','brittle_nails','swollen_extremeties','excessive_hunger','extra_marital_contacts',\n",
    "'drying_and_tingling_lips','slurred_speech','knee_pain','hip_joint_pain','muscle_weakness','swelling_joints',\n",
    "'movement_stiffness','spinning_movements','unsteadiness','weakness_of_one_body_side','loss_of_smell','bladder_discomfort',\n",
    "'foul_smell_of urine','continuous_feel_of_urine','passage_of_gases','internal_itching','toxic_look_(typhos)','depression','irritability',\n",
    "'altered_sensorium','red_spots_over_body','belly_pain','abnormal_menstruation','dischromic _patches','watering_from_eyes','increased_appetite',\n",
    "'polyuria','family_history','mucoid_sputum','rusty_sputum','lack_of_concentration','visual_disturbances','receiving_blood_transfusion',\n",
    "'receiving_unsterile_injections','coma','stomach_bleeding','distention_of_abdomen','history_of_alcohol_consumption','fluid_overload.1','blood_in_sputum',\n",
    "'prominent_veins_on_calf','palpitations','painful_walking','pus_filled_pimples','blackheads','scurring','skin_peeling','silver_like_dusting','small_dents_in_nails',\n",
    "'inflammatory_nails','blister','red_sore_around_nose','yellow_crust_ooze'],axis = 1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c539366d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4920 entries, 0 to 4919\n",
      "Data columns (total 30 columns):\n",
      " #   Column                        Non-Null Count  Dtype \n",
      "---  ------                        --------------  ----- \n",
      " 0   itching                       4920 non-null   int64 \n",
      " 1   skin_rash                     4920 non-null   int64 \n",
      " 2   chills                        4920 non-null   int64 \n",
      " 3   joint_pain                    4920 non-null   int64 \n",
      " 4   vomiting                      4920 non-null   int64 \n",
      " 5   fatigue                       4920 non-null   int64 \n",
      " 6   weight_loss                   4920 non-null   int64 \n",
      " 7   lethargy                      4920 non-null   int64 \n",
      " 8   cough                         4920 non-null   int64 \n",
      " 9   high_fever                    4920 non-null   int64 \n",
      " 10  breathlessness                4920 non-null   int64 \n",
      " 11  headache                      4920 non-null   int64 \n",
      " 12  yellowish_skin                4920 non-null   int64 \n",
      " 13  dark_urine                    4920 non-null   int64 \n",
      " 14  nausea                        4920 non-null   int64 \n",
      " 15  loss_of_appetite              4920 non-null   int64 \n",
      " 16  abdominal_pain                4920 non-null   int64 \n",
      " 17  diarrhoea                     4920 non-null   int64 \n",
      " 18  mild_fever                    4920 non-null   int64 \n",
      " 19  yellowing_of_eyes             4920 non-null   int64 \n",
      " 20  swelled_lymph_nodes           4920 non-null   int64 \n",
      " 21  malaise                       4920 non-null   int64 \n",
      " 22  blurred_and_distorted_vision  4920 non-null   int64 \n",
      " 23  phlegm                        4920 non-null   int64 \n",
      " 24  chest_pain                    4920 non-null   int64 \n",
      " 25  dizziness                     4920 non-null   int64 \n",
      " 26  stiff_neck                    4920 non-null   int64 \n",
      " 27  loss_of_balance               4920 non-null   int64 \n",
      " 28  muscle_pain                   4920 non-null   int64 \n",
      " 29  prognosis                     4920 non-null   object\n",
      "dtypes: int64(29), object(1)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "164441b1",
   "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>itching</th>\n",
       "      <th>skin_rash</th>\n",
       "      <th>chills</th>\n",
       "      <th>joint_pain</th>\n",
       "      <th>vomiting</th>\n",
       "      <th>fatigue</th>\n",
       "      <th>weight_loss</th>\n",
       "      <th>lethargy</th>\n",
       "      <th>cough</th>\n",
       "      <th>high_fever</th>\n",
       "      <th>...</th>\n",
       "      <th>yellowing_of_eyes</th>\n",
       "      <th>swelled_lymph_nodes</th>\n",
       "      <th>malaise</th>\n",
       "      <th>blurred_and_distorted_vision</th>\n",
       "      <th>phlegm</th>\n",
       "      <th>chest_pain</th>\n",
       "      <th>dizziness</th>\n",
       "      <th>stiff_neck</th>\n",
       "      <th>loss_of_balance</th>\n",
       "      <th>muscle_pain</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</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>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</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>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</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>...</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>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>4915</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>...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4916</th>\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>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4917</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>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4918</th>\n",
       "      <td>0</td>\n",
       "      <td>1</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>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4919</th>\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>1</td>\n",
       "      <td>...</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>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4920 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      itching  skin_rash  chills  joint_pain  vomiting  fatigue  weight_loss  \\\n",
       "0           1          1       0           0         0        0            0   \n",
       "1           0          1       0           0         0        0            0   \n",
       "2           1          0       0           0         0        0            0   \n",
       "3           1          1       0           0         0        0            0   \n",
       "4           1          1       0           0         0        0            0   \n",
       "...       ...        ...     ...         ...       ...      ...          ...   \n",
       "4915        0          0       0           0         1        0            0   \n",
       "4916        0          1       0           0         0        0            0   \n",
       "4917        0          0       0           0         0        0            0   \n",
       "4918        0          1       0           1         0        0            0   \n",
       "4919        0          1       0           0         0        0            0   \n",
       "\n",
       "      lethargy  cough  high_fever  ...  yellowing_of_eyes  \\\n",
       "0            0      0           0  ...                  0   \n",
       "1            0      0           0  ...                  0   \n",
       "2            0      0           0  ...                  0   \n",
       "3            0      0           0  ...                  0   \n",
       "4            0      0           0  ...                  0   \n",
       "...        ...    ...         ...  ...                ...   \n",
       "4915         0      0           0  ...                  0   \n",
       "4916         0      0           0  ...                  0   \n",
       "4917         0      0           0  ...                  0   \n",
       "4918         0      0           0  ...                  0   \n",
       "4919         0      0           1  ...                  0   \n",
       "\n",
       "      swelled_lymph_nodes  malaise  blurred_and_distorted_vision  phlegm  \\\n",
       "0                       0        0                             0       0   \n",
       "1                       0        0                             0       0   \n",
       "2                       0        0                             0       0   \n",
       "3                       0        0                             0       0   \n",
       "4                       0        0                             0       0   \n",
       "...                   ...      ...                           ...     ...   \n",
       "4915                    0        0                             0       0   \n",
       "4916                    0        0                             0       0   \n",
       "4917                    0        0                             0       0   \n",
       "4918                    0        0                             0       0   \n",
       "4919                    0        0                             0       0   \n",
       "\n",
       "      chest_pain  dizziness  stiff_neck  loss_of_balance  muscle_pain  \n",
       "0              0          0           0                0            0  \n",
       "1              0          0           0                0            0  \n",
       "2              0          0           0                0            0  \n",
       "3              0          0           0                0            0  \n",
       "4              0          0           0                0            0  \n",
       "...          ...        ...         ...              ...          ...  \n",
       "4915           0          0           0                1            0  \n",
       "4916           0          0           0                0            0  \n",
       "4917           0          0           0                0            0  \n",
       "4918           0          0           0                0            0  \n",
       "4919           0          0           0                0            0  \n",
       "\n",
       "[4920 rows x 29 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=df.iloc[:,0:29]\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f6237ac3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([15, 15, 15, ..., 38, 35, 27])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import preprocessing\n",
    "le = preprocessing.LabelEncoder()\n",
    "le.fit_transform(y)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "77b666ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.20, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4acf79cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9176829268292683"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "logreg = LogisticRegression(random_state = 42,max_iter=1000)\n",
    "logreg.fit(x_train, y_train)\n",
    "y_pred=logreg.predict(x_test)\n",
    "logreg.score(x_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7fb5532c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Lenovo\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but LogisticRegression was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array(['hepatitis A'], dtype=object)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "logreg.predict([[0,0,0,0,1,0,0,0,0,0,1,0,1,1,1,0,1,0,0,1,0,0,0,1,0,0,0,0,1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "04f1a656",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open('model_pkl', 'wb') as files:\n",
    "    pickle.dump(logreg, files)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1bf15f20",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('model_pkl' , 'rb') as f:\n",
    "    lr = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "296f81c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Lenovo\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but LogisticRegression was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array(['hepatitis A'], dtype=object)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.predict([[0,0,0,0,1,0,0,0,0,0,1,0,1,1,1,0,1,0,0,1,0,0,0,1,0,0,0,0,1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "800e0c17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Fungal infection', 'Allergy', 'GERD', 'Chronic cholestasis',\n",
       "       'Drug Reaction', 'Peptic ulcer diseae', 'AIDS', 'Diabetes ',\n",
       "       'Gastroenteritis', 'Bronchial Asthma', 'Hypertension ', 'Migraine',\n",
       "       'Cervical spondylosis', 'Paralysis (brain hemorrhage)', 'Jaundice',\n",
       "       'Malaria', 'Chicken pox', 'Dengue', 'Typhoid', 'hepatitis A',\n",
       "       'Hepatitis B', 'Hepatitis C', 'Hepatitis D', 'Hepatitis E',\n",
       "       'Alcoholic hepatitis', 'Tuberculosis', 'Common Cold', 'Pneumonia',\n",
       "       'Dimorphic hemmorhoids(piles)', 'Heart attack', 'Varicose veins',\n",
       "       'Hypothyroidism', 'Hyperthyroidism', 'Hypoglycemia',\n",
       "       'Osteoarthristis', 'Arthritis',\n",
       "       '(vertigo) Paroymsal  Positional Vertigo', 'Acne',\n",
       "       'Urinary tract infection', 'Psoriasis', 'Impetigo'], dtype=object)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "63eb6261",
   "metadata": {},
   "outputs": [],
   "source": [
    "n=len(y.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b183d43a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4871953",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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