Support Vector Regression(2020).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8fbcca8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "af86426f",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = pd.read_excel(r'DataFinal17-20.xlsx',sheet_name='2020')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9d69a5b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = dataset.drop(['Total'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3684297c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    SrNo     District  Homicide/Murder  Causing death by negligence  Hurt  \\\n",
      "0      1   Ahmednagar              254                          620  1826   \n",
      "1      2        Akola              114                          116  1345   \n",
      "2      3     Amravati              201                          354  2133   \n",
      "3      4    Aurangbad              139                          386  1869   \n",
      "4      5         Beed              206                          308  1233   \n",
      "5      6     Bhandara               41                          141   486   \n",
      "6      7     Buldhana              122                          293  2099   \n",
      "7      8   Chandrapur              105                          234  1147   \n",
      "8      9        Dhule               84                          352   433   \n",
      "9     10   Gadchiroli               65                          135   303   \n",
      "10    11       Gondia               50                          131   311   \n",
      "11    12      Hingoli               75                          119   649   \n",
      "12    13      Jalgaon              192                          439   901   \n",
      "13    14        Jalna              133                          209  1436   \n",
      "14    15     Kolhapur              146                          313  1020   \n",
      "15    16        Latur              104                          244  1077   \n",
      "16    17       Mumbai              521                          349  4171   \n",
      "17    18       Nagpur              299                          581  2252   \n",
      "18    19       Nanded              143                          252  1778   \n",
      "19    20    Nandurbar               62                          133   255   \n",
      "20    21        Nasik              240                          917  1720   \n",
      "21    22  Navi Mumbai               79                          232   466   \n",
      "22    23    Osmanabad               92                          253   847   \n",
      "23    24     Parbhani              165                          121  1227   \n",
      "24    25         Pune              649                         1102  3540   \n",
      "25    26       Raigad               47                          191   334   \n",
      "26    27    Ratnagiri               39                          106   250   \n",
      "27    28       Sangli              207                          269  1344   \n",
      "28    29       Satara              145                          359  1017   \n",
      "29    30   Sindhudurg               18                           50   241   \n",
      "30    31      Solapur              246                          461  2437   \n",
      "31    32        Thane              336                          814  3187   \n",
      "32    33       Wardha               86                          170  1394   \n",
      "33    34       Washim              114                          110   855   \n",
      "34    35     Yavatmal              140                          310  1431   \n",
      "\n",
      "    Assault on woman  Kidnapping and abduction  Human trafficking   Rape  \\\n",
      "0                543                       369                   0    92   \n",
      "1                245                        76                   0    28   \n",
      "2                461                       190                   0    97   \n",
      "3                335                       242                   0    80   \n",
      "4                248                        91                   0    50   \n",
      "5                 88                        71                   0    16   \n",
      "6                313                       110                   0    36   \n",
      "7                194                       152                   1    46   \n",
      "8                 80                        98                   1    14   \n",
      "9                 55                        32                   0    17   \n",
      "10                57                        40                   0    18   \n",
      "11                73                        27                   0    15   \n",
      "12               259                       187                   0    34   \n",
      "13               208                       100                   0    36   \n",
      "14               263                       150                  15    54   \n",
      "15               138                       111                   3    26   \n",
      "16              1553                      1180                  58   331   \n",
      "17               386                       442                  13   120   \n",
      "18               232                       127                   1    40   \n",
      "19                44                        57                   0    17   \n",
      "20               384                       473                   1    65   \n",
      "21               158                       217                   4    62   \n",
      "22               123                        87                   0    21   \n",
      "23               139                        65                   0    33   \n",
      "24               936                      1113                  28   243   \n",
      "25                77                        73                   0    20   \n",
      "26                53                        43                   0    11   \n",
      "27               250                       228                   2    39   \n",
      "28               275                       192                   2    49   \n",
      "29                53                        18                   0     6   \n",
      "30               449                       276                   8    96   \n",
      "31               746                      1159                  30   243   \n",
      "32               197                       113                   0    25   \n",
      "33               163                        66                   0    24   \n",
      "34               187                       128                   1    44   \n",
      "\n",
      "    Offence against public tranquility  ...  Miscellaneous  Others  \\\n",
      "0                                  905  ...          30535     221   \n",
      "1                                  111  ...           4244     213   \n",
      "2                                  144  ...           3921     164   \n",
      "3                                  428  ...           4292     411   \n",
      "4                                  508  ...           1858     111   \n",
      "5                                   43  ...           1051      54   \n",
      "6                                  320  ...           3024     104   \n",
      "7                                   84  ...           2235     355   \n",
      "8                                  205  ...           1237     175   \n",
      "9                                   21  ...            427      27   \n",
      "10                                  23  ...            996     134   \n",
      "11                                 140  ...           1314      30   \n",
      "12                                 440  ...           4353     256   \n",
      "13                                 411  ...           1164     770   \n",
      "14                                 388  ...           5190     202   \n",
      "15                                 303  ...           2000      82   \n",
      "16                                 392  ...          19788    9146   \n",
      "17                                 199  ...           9647     312   \n",
      "18                                 307  ...           2970      86   \n",
      "19                                 116  ...           2930    3053   \n",
      "20                                 637  ...          18068     347   \n",
      "21                                  95  ...           1827      85   \n",
      "22                                 247  ...           1126      61   \n",
      "23                                 119  ...           1468      84   \n",
      "24                                1227  ...          37271     771   \n",
      "25                                 165  ...            474     105   \n",
      "26                                 109  ...            388      18   \n",
      "27                                 340  ...           1756     293   \n",
      "28                                 481  ...           2986     162   \n",
      "29                                  43  ...            330      14   \n",
      "30                                 786  ...           2906    3744   \n",
      "31                                 687  ...           8009     997   \n",
      "32                                  44  ...           1980      24   \n",
      "33                                 142  ...           3699      29   \n",
      "34                                  85  ...           4117     138   \n",
      "\n",
      "    Population  Crime Rate  Sex Ratio  Literacy  Density   Latitude  \\\n",
      "0      4543159    0.851588        939    0.7905      266  19.094829   \n",
      "1      1813906    0.414795        946    0.8805      320  20.700216   \n",
      "2      2888445    0.350119        951    0.8738      237  20.931982   \n",
      "3      3701282    0.331453        923    0.7902      366  19.876165   \n",
      "4      2585049    0.221234        916    0.7699      242  18.990088   \n",
      "5      1200334    0.227187        982    0.8376      294  21.177658   \n",
      "6      2586258    0.301285        934    0.8340      268  20.529215   \n",
      "7      2204307    0.255908        961    0.8001      193  19.961540   \n",
      "8      2050862    0.172464        946    0.7280      285  20.904220   \n",
      "9      1072942    0.132812        982    0.7436       74  20.184871   \n",
      "10     1322507    0.165595        999    0.8495      253  21.454948   \n",
      "11     1177345    0.247421        942    0.7817      244  19.717370   \n",
      "12     4229917    0.221139        925    0.7820      360  21.007658   \n",
      "13     1959046    0.319288        937    0.7152      254  19.834666   \n",
      "14     3876001    0.240454        957    0.8151      504  16.704987   \n",
      "15     2454196    0.209682        928    0.7726      343  18.408793   \n",
      "16    12442373    0.469717        846    0.8956    20316  19.075984   \n",
      "17     4653570    0.425458        951    0.8839      470  19.153823   \n",
      "18     3361292    0.223545        943    0.7545      319  21.145800   \n",
      "19     1648295    0.432811        978    0.6438      277  19.138251   \n",
      "20     6107187    0.424238        934    0.8231      393  21.746855   \n",
      "21     1120547    0.498328        837    0.8962     6204  19.997453   \n",
      "22     1657576    0.218512        924    0.7844      219  18.185332   \n",
      "23     1836086    0.241764        947    0.7334      295  19.260838   \n",
      "24     9429408    0.591914        915    0.8615      603  18.520430   \n",
      "25     2634200    0.081998        959    0.8314      368  18.237628   \n",
      "26     1615069    0.092318       1122    0.8218      197  16.990215   \n",
      "27     2822143    0.233971        966    0.8148      329  16.852397   \n",
      "28     3003741    0.246626        988    0.8287      287  17.680464   \n",
      "29      849651    0.117578       1036    0.8556      163  16.349219   \n",
      "30     4317756    0.341474        938    0.7702      290  17.659919   \n",
      "31    11060148    0.213632        886    0.8453     1157  19.218331   \n",
      "32     1300774    0.373777        946    0.8699      206  20.745319   \n",
      "33     1197160    0.475292        930    0.8325      244  20.111912   \n",
      "34     2772348    0.272693        952    0.8282      204  20.389938   \n",
      "\n",
      "    Longitude  cluster  \n",
      "0   74.747979        0  \n",
      "1   77.008168        1  \n",
      "2   77.752304        1  \n",
      "3   75.343314        1  \n",
      "4   75.753132        1  \n",
      "5   79.657013        1  \n",
      "6   76.184170        1  \n",
      "7   79.296147        1  \n",
      "8   74.774898        1  \n",
      "9   79.994796        1  \n",
      "10  80.196071        1  \n",
      "11  77.149372        1  \n",
      "12  75.562604        1  \n",
      "13  75.881635        1  \n",
      "14  74.243253        1  \n",
      "15  76.560383        1  \n",
      "16  72.877656        2  \n",
      "17  72.875179        0  \n",
      "18  79.088155        1  \n",
      "19  77.320955        1  \n",
      "20  74.123996        0  \n",
      "21  73.789802        1  \n",
      "22  76.041964        1  \n",
      "23  76.774776        1  \n",
      "24  73.856744        3  \n",
      "25  73.444539        1  \n",
      "26  73.312023        1  \n",
      "27  74.581477        1  \n",
      "28  74.018261        1  \n",
      "29  73.559413        1  \n",
      "30  75.906391        0  \n",
      "31  72.978090        3  \n",
      "32  78.602195        1  \n",
      "33  77.131259        1  \n",
      "34  78.130685        1  \n",
      "\n",
      "[35 rows x 22 columns]\n"
     ]
    }
   ],
   "source": [
    "print(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2dbeae1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = dataset.iloc[:, 2:14].values\n",
    "y = dataset.iloc[:, 19:20].values\n",
    "y2 = dataset.iloc[:, 20:21].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "549760e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  254   620  1826   543   369     0    92   905  3104   220 30535   221]\n",
      " [  114   116  1345   245    76     0    28   111   946    86  4244   213]\n",
      " [  201   354  2133   461   190     0    97   144  2198   250  3921   164]\n",
      " [  139   386  1869   335   242     0    80   428  3821   265  4292   411]\n",
      " [  206   308  1233   248    91     0    50   508  1002   104  1858   111]\n",
      " [   41   141   486    88    71     0    16    43   676    60  1051    54]\n",
      " [  122   293  2099   313   110     0    36   320  1269   102  3024   104]\n",
      " [  105   234  1147   194   152     1    46    84   980   108  2235   355]\n",
      " [   84   352   433    80    98     1    14   205   781    77  1237   175]\n",
      " [   65   135   303    55    32     0    17    21   302    41   427    27]\n",
      " [   50   131   311    57    40     0    18    23   400    30   996   134]\n",
      " [   75   119   649    73    27     0    15   140   436    35  1314    30]\n",
      " [  192   439   901   259   187     0    34   440  2045   248  4353   256]\n",
      " [  133   209  1436   208   100     0    36   411  1618   170  1164   770]\n",
      " [  146   313  1020   263   150    15    54   388  1357   222  5190   202]\n",
      " [  104   244  1077   138   111     3    26   303   964    94  2000    82]\n",
      " [  521   349  4171  1553  1180    58   331   392 17530  3425 19788  9146]\n",
      " [  299   581  2252   386   442    13   120   199  4980   568  9647   312]\n",
      " [  143   252  1778   232   127     1    40   307  1464   114  2970    86]\n",
      " [   62   133   255    44    57     0    17   116   429    38  2930  3053]\n",
      " [  240   917  1720   384   473     1    65   637  2528   529 18068   347]\n",
      " [   79   232   466   158   217     4    62    95  1859   500  1827    85]\n",
      " [   92   253   847   123    87     0    21   247   685    80  1126    61]\n",
      " [  165   121  1227   139    65     0    33   119   924    94  1468    84]\n",
      " [  649  1102  3540   936  1113    28   243  1227  7935   999 37271   771]\n",
      " [   47   191   334    77    73     0    20   165   533   141   474   105]\n",
      " [   39   106   250    53    43     0    11   109   361   113   388    18]\n",
      " [  207   269  1344   250   228     2    39   340  1678   197  1756   293]\n",
      " [  145   359  1017   275   192     2    49   481  1557   183  2986   162]\n",
      " [   18    50   241    53    18     0     6    43   178    48   330    14]\n",
      " [  246   461  2437   449   276     8    96   786  3046   289  2906  3744]\n",
      " [  336   814  3187   746  1159    30   243   687  6209  1211  8009   997]\n",
      " [   86   170  1394   197   113     0    25    44   741    88  1980    24]\n",
      " [  114   110   855   163    66     0    24   142   449    39  3699    29]\n",
      " [  140   310  1431   187   128     1    44    85   923    56  4117   138]]\n"
     ]
    }
   ],
   "source": [
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "80ea443c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[19.0948287]\n",
      " [20.7002159]\n",
      " [20.9319821]\n",
      " [19.8761653]\n",
      " [18.990088 ]\n",
      " [21.177658 ]\n",
      " [20.5292147]\n",
      " [19.9615398]\n",
      " [20.9042201]\n",
      " [20.184871 ]\n",
      " [21.4549477]\n",
      " [19.7173703]\n",
      " [21.0076578]\n",
      " [19.8346659]\n",
      " [16.7049873]\n",
      " [18.4087934]\n",
      " [19.0759837]\n",
      " [19.1538231]\n",
      " [21.1458004]\n",
      " [19.1382514]\n",
      " [21.7468548]\n",
      " [19.9974533]\n",
      " [18.185332 ]\n",
      " [19.2608384]\n",
      " [18.5204303]\n",
      " [18.2376278]\n",
      " [16.990215 ]\n",
      " [16.8523973]\n",
      " [17.6804639]\n",
      " [16.3492193]\n",
      " [17.6599188]\n",
      " [19.2183307]\n",
      " [20.745319 ]\n",
      " [20.1119123]\n",
      " [20.3899385]]\n"
     ]
    }
   ],
   "source": [
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "783c1bc7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[74.7479789]\n",
      " [77.0081678]\n",
      " [77.7523039]\n",
      " [75.3433139]\n",
      " [75.7531324]\n",
      " [79.6570127]\n",
      " [76.1841701]\n",
      " [79.2961468]\n",
      " [74.7748979]\n",
      " [79.9947956]\n",
      " [80.1960712]\n",
      " [77.1493722]\n",
      " [75.5626039]\n",
      " [75.8816345]\n",
      " [74.2432527]\n",
      " [76.5603828]\n",
      " [72.8776559]\n",
      " [72.8751786]\n",
      " [79.0881546]\n",
      " [77.3209555]\n",
      " [74.123996 ]\n",
      " [73.7898023]\n",
      " [76.0419642]\n",
      " [76.774776 ]\n",
      " [73.8567437]\n",
      " [73.4445392]\n",
      " [73.3120233]\n",
      " [74.5814773]\n",
      " [74.018261 ]\n",
      " [73.5594128]\n",
      " [75.9063906]\n",
      " [72.9780897]\n",
      " [78.6021946]\n",
      " [77.1312586]\n",
      " [78.1306846]]\n"
     ]
    }
   ],
   "source": [
    "print(y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "97be30de",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    SrNo     District  Homicide/Murder  Causing death by negligence  Hurt  \\\n",
      "0      1   Ahmednagar              254                          620  1826   \n",
      "1      2        Akola              114                          116  1345   \n",
      "2      3     Amravati              201                          354  2133   \n",
      "3      4    Aurangbad              139                          386  1869   \n",
      "4      5         Beed              206                          308  1233   \n",
      "5      6     Bhandara               41                          141   486   \n",
      "6      7     Buldhana              122                          293  2099   \n",
      "7      8   Chandrapur              105                          234  1147   \n",
      "8      9        Dhule               84                          352   433   \n",
      "9     10   Gadchiroli               65                          135   303   \n",
      "10    11       Gondia               50                          131   311   \n",
      "11    12      Hingoli               75                          119   649   \n",
      "12    13      Jalgaon              192                          439   901   \n",
      "13    14        Jalna              133                          209  1436   \n",
      "14    15     Kolhapur              146                          313  1020   \n",
      "15    16        Latur              104                          244  1077   \n",
      "16    17       Mumbai              521                          349  4171   \n",
      "17    18       Nagpur              299                          581  2252   \n",
      "18    19       Nanded              143                          252  1778   \n",
      "19    20    Nandurbar               62                          133   255   \n",
      "20    21        Nasik              240                          917  1720   \n",
      "21    22  Navi Mumbai               79                          232   466   \n",
      "22    23    Osmanabad               92                          253   847   \n",
      "23    24     Parbhani              165                          121  1227   \n",
      "24    25         Pune              649                         1102  3540   \n",
      "25    26       Raigad               47                          191   334   \n",
      "26    27    Ratnagiri               39                          106   250   \n",
      "27    28       Sangli              207                          269  1344   \n",
      "28    29       Satara              145                          359  1017   \n",
      "29    30   Sindhudurg               18                           50   241   \n",
      "30    31      Solapur              246                          461  2437   \n",
      "31    32        Thane              336                          814  3187   \n",
      "32    33       Wardha               86                          170  1394   \n",
      "33    34       Washim              114                          110   855   \n",
      "34    35     Yavatmal              140                          310  1431   \n",
      "\n",
      "    Assault on woman  Kidnapping and abduction  Human trafficking   Rape  \\\n",
      "0                543                       369                   0    92   \n",
      "1                245                        76                   0    28   \n",
      "2                461                       190                   0    97   \n",
      "3                335                       242                   0    80   \n",
      "4                248                        91                   0    50   \n",
      "5                 88                        71                   0    16   \n",
      "6                313                       110                   0    36   \n",
      "7                194                       152                   1    46   \n",
      "8                 80                        98                   1    14   \n",
      "9                 55                        32                   0    17   \n",
      "10                57                        40                   0    18   \n",
      "11                73                        27                   0    15   \n",
      "12               259                       187                   0    34   \n",
      "13               208                       100                   0    36   \n",
      "14               263                       150                  15    54   \n",
      "15               138                       111                   3    26   \n",
      "16              1553                      1180                  58   331   \n",
      "17               386                       442                  13   120   \n",
      "18               232                       127                   1    40   \n",
      "19                44                        57                   0    17   \n",
      "20               384                       473                   1    65   \n",
      "21               158                       217                   4    62   \n",
      "22               123                        87                   0    21   \n",
      "23               139                        65                   0    33   \n",
      "24               936                      1113                  28   243   \n",
      "25                77                        73                   0    20   \n",
      "26                53                        43                   0    11   \n",
      "27               250                       228                   2    39   \n",
      "28               275                       192                   2    49   \n",
      "29                53                        18                   0     6   \n",
      "30               449                       276                   8    96   \n",
      "31               746                      1159                  30   243   \n",
      "32               197                       113                   0    25   \n",
      "33               163                        66                   0    24   \n",
      "34               187                       128                   1    44   \n",
      "\n",
      "    Offence against public tranquility  ...  Miscellaneous  Others  \\\n",
      "0                                  905  ...          30535     221   \n",
      "1                                  111  ...           4244     213   \n",
      "2                                  144  ...           3921     164   \n",
      "3                                  428  ...           4292     411   \n",
      "4                                  508  ...           1858     111   \n",
      "5                                   43  ...           1051      54   \n",
      "6                                  320  ...           3024     104   \n",
      "7                                   84  ...           2235     355   \n",
      "8                                  205  ...           1237     175   \n",
      "9                                   21  ...            427      27   \n",
      "10                                  23  ...            996     134   \n",
      "11                                 140  ...           1314      30   \n",
      "12                                 440  ...           4353     256   \n",
      "13                                 411  ...           1164     770   \n",
      "14                                 388  ...           5190     202   \n",
      "15                                 303  ...           2000      82   \n",
      "16                                 392  ...          19788    9146   \n",
      "17                                 199  ...           9647     312   \n",
      "18                                 307  ...           2970      86   \n",
      "19                                 116  ...           2930    3053   \n",
      "20                                 637  ...          18068     347   \n",
      "21                                  95  ...           1827      85   \n",
      "22                                 247  ...           1126      61   \n",
      "23                                 119  ...           1468      84   \n",
      "24                                1227  ...          37271     771   \n",
      "25                                 165  ...            474     105   \n",
      "26                                 109  ...            388      18   \n",
      "27                                 340  ...           1756     293   \n",
      "28                                 481  ...           2986     162   \n",
      "29                                  43  ...            330      14   \n",
      "30                                 786  ...           2906    3744   \n",
      "31                                 687  ...           8009     997   \n",
      "32                                  44  ...           1980      24   \n",
      "33                                 142  ...           3699      29   \n",
      "34                                  85  ...           4117     138   \n",
      "\n",
      "    Population  Crime Rate  Sex Ratio  Literacy  Density   Latitude  \\\n",
      "0      4543159    0.851588        939    0.7905      266  19.094829   \n",
      "1      1813906    0.414795        946    0.8805      320  20.700216   \n",
      "2      2888445    0.350119        951    0.8738      237  20.931982   \n",
      "3      3701282    0.331453        923    0.7902      366  19.876165   \n",
      "4      2585049    0.221234        916    0.7699      242  18.990088   \n",
      "5      1200334    0.227187        982    0.8376      294  21.177658   \n",
      "6      2586258    0.301285        934    0.8340      268  20.529215   \n",
      "7      2204307    0.255908        961    0.8001      193  19.961540   \n",
      "8      2050862    0.172464        946    0.7280      285  20.904220   \n",
      "9      1072942    0.132812        982    0.7436       74  20.184871   \n",
      "10     1322507    0.165595        999    0.8495      253  21.454948   \n",
      "11     1177345    0.247421        942    0.7817      244  19.717370   \n",
      "12     4229917    0.221139        925    0.7820      360  21.007658   \n",
      "13     1959046    0.319288        937    0.7152      254  19.834666   \n",
      "14     3876001    0.240454        957    0.8151      504  16.704987   \n",
      "15     2454196    0.209682        928    0.7726      343  18.408793   \n",
      "16    12442373    0.469717        846    0.8956    20316  19.075984   \n",
      "17     4653570    0.425458        951    0.8839      470  19.153823   \n",
      "18     3361292    0.223545        943    0.7545      319  21.145800   \n",
      "19     1648295    0.432811        978    0.6438      277  19.138251   \n",
      "20     6107187    0.424238        934    0.8231      393  21.746855   \n",
      "21     1120547    0.498328        837    0.8962     6204  19.997453   \n",
      "22     1657576    0.218512        924    0.7844      219  18.185332   \n",
      "23     1836086    0.241764        947    0.7334      295  19.260838   \n",
      "24     9429408    0.591914        915    0.8615      603  18.520430   \n",
      "25     2634200    0.081998        959    0.8314      368  18.237628   \n",
      "26     1615069    0.092318       1122    0.8218      197  16.990215   \n",
      "27     2822143    0.233971        966    0.8148      329  16.852397   \n",
      "28     3003741    0.246626        988    0.8287      287  17.680464   \n",
      "29      849651    0.117578       1036    0.8556      163  16.349219   \n",
      "30     4317756    0.341474        938    0.7702      290  17.659919   \n",
      "31    11060148    0.213632        886    0.8453     1157  19.218331   \n",
      "32     1300774    0.373777        946    0.8699      206  20.745319   \n",
      "33     1197160    0.475292        930    0.8325      244  20.111912   \n",
      "34     2772348    0.272693        952    0.8282      204  20.389938   \n",
      "\n",
      "    Longitude  cluster  \n",
      "0   74.747979        0  \n",
      "1   77.008168        1  \n",
      "2   77.752304        1  \n",
      "3   75.343314        1  \n",
      "4   75.753132        1  \n",
      "5   79.657013        1  \n",
      "6   76.184170        1  \n",
      "7   79.296147        1  \n",
      "8   74.774898        1  \n",
      "9   79.994796        1  \n",
      "10  80.196071        1  \n",
      "11  77.149372        1  \n",
      "12  75.562604        1  \n",
      "13  75.881635        1  \n",
      "14  74.243253        1  \n",
      "15  76.560383        1  \n",
      "16  72.877656        2  \n",
      "17  72.875179        0  \n",
      "18  79.088155        1  \n",
      "19  77.320955        1  \n",
      "20  74.123996        0  \n",
      "21  73.789802        1  \n",
      "22  76.041964        1  \n",
      "23  76.774776        1  \n",
      "24  73.856744        3  \n",
      "25  73.444539        1  \n",
      "26  73.312023        1  \n",
      "27  74.581477        1  \n",
      "28  74.018261        1  \n",
      "29  73.559413        1  \n",
      "30  75.906391        0  \n",
      "31  72.978090        3  \n",
      "32  78.602195        1  \n",
      "33  77.131259        1  \n",
      "34  78.130685        1  \n",
      "\n",
      "[35 rows x 22 columns]\n"
     ]
    }
   ],
   "source": [
    "print(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8a3516a3",
   "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 = 0.2, random_state = 0)\n",
    "X_train, X_test, y2_train, y2_test = train_test_split(X, y2, test_size = 0.2, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9c2bd649",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature Scaling\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "sc_X = StandardScaler()\n",
    "sc_y = StandardScaler()\n",
    "sc_y2 = StandardScaler()\n",
    "X = sc_X.fit_transform(X)\n",
    "y = sc_y.fit_transform(y)\n",
    "y2 = sc_y2.fit_transform(y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "69962b72",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\welcome\\appdata\\local\\programs\\python\\python39\\lib\\site-packages\\sklearn\\utils\\validation.py:63: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  return f(*args, **kwargs)\n",
      "c:\\users\\welcome\\appdata\\local\\programs\\python\\python39\\lib\\site-packages\\sklearn\\utils\\validation.py:63: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  return f(*args, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "# Fitting SVR to the dataset\n",
    "from sklearn.svm import SVR\n",
    "regressor = SVR(kernel = 'rbf')\n",
    "#rbf = Gaussian Radial Basis Function Kernel\n",
    "yfit = regressor.fit(X, y)\n",
    "y2fit =regressor.fit(X, y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "779eb46b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Predicting a new result\n",
    "\n",
    "y_pred = regressor.predict(sc_X.transform(np.array([[254,620,1826,543,369,0,92,905,3104,220,30535,221]])))\n",
    "y_pred2 = regressor.predict(sc_X.transform(np.array([[254,620,1826,543,369,0,92,905,3104,220,30535,221]])))\n",
    "\n",
    "\n",
    "y2_pred = regressor.predict(sc_X.transform(np.array([[84,352,433,80,98,1,14,205,781,77,1237,175]])))\n",
    "y2_pred2 = regressor.predict(sc_X.transform(np.array([[84,352,433,80,98,1,14,205,781,77,1237,175]])))\n",
    "\n",
    "\n",
    "y3_pred = regressor.predict(sc_X.transform(np.array([[62,133,255,44,57,0,17,116,429,38,2930,3053]])))\n",
    "y3_pred2 = regressor.predict(sc_X.transform(np.array([[62,133,255,44,57,0,17,116,429,38,2930,3053]])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "708d8cbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = sc_y.inverse_transform(np.array(y_pred).reshape(1,-1))\n",
    "y_pred2 = sc_y2.inverse_transform(np.array(y_pred2).reshape(1,-1))\n",
    "\n",
    "y2_pred = sc_y.inverse_transform(np.array(y2_pred).reshape(1,-1))\n",
    "y2_pred2 = sc_y2.inverse_transform(np.array(y2_pred2).reshape(1,-1))\n",
    "\n",
    "y3_pred = sc_y.inverse_transform(np.array(y3_pred).reshape(1,-1))\n",
    "y3_pred2 = sc_y2.inverse_transform(np.array(y3_pred2).reshape(1,-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2a347d09",
   "metadata": {},
   "outputs": [],
   "source": [
    "def district_pred(a,b):\n",
    "    target_district = \"\"\n",
    "    min = 999\n",
    "    num = 0\n",
    "    for i in range(len(dataset['Latitude'])):\n",
    "            if (abs(a-dataset['Latitude'][i])+abs(b-dataset['Longitude'][i]))<min:\n",
    "                min = abs(a-dataset['Latitude'][i])+abs(b-dataset['Longitude'][i])\n",
    "                target_district = dataset['District'][i]\n",
    "                num = i\n",
    "    return target_district,num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0711c35d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pune\n",
      "18.5204303\n",
      "73.8567437\n",
      "Jalna\n",
      "19.8346659\n",
      "75.8816345\n",
      "Washim\n",
      "20.1119123\n",
      "77.1312586\n"
     ]
    }
   ],
   "source": [
    "y_preds = [y_pred,y2_pred,y3_pred]\n",
    "y_pred2s = [y_pred2,y2_pred2,y3_pred2]\n",
    "\n",
    "for i in range(len(y_preds)):\n",
    "    str, x = district_pred(y_preds[i],y_pred2s[i])\n",
    "    print(str)\n",
    "    print(dataset['Latitude'][x])\n",
    "    print(dataset['Longitude'][x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "990d7f40",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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