k-NN.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.neighbors import KNeighborsClassifier as knn\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"E:/Academics/data/wisc_bc_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>diagnosis</th>\n",
       "      <th>radius_mean</th>\n",
       "      <th>texture_mean</th>\n",
       "      <th>perimeter_mean</th>\n",
       "      <th>area_mean</th>\n",
       "      <th>smoothness_mean</th>\n",
       "      <th>compactness_mean</th>\n",
       "      <th>concavity_mean</th>\n",
       "      <th>points_mean</th>\n",
       "      <th>...</th>\n",
       "      <th>radius_worst</th>\n",
       "      <th>texture_worst</th>\n",
       "      <th>perimeter_worst</th>\n",
       "      <th>area_worst</th>\n",
       "      <th>smoothness_worst</th>\n",
       "      <th>compactness_worst</th>\n",
       "      <th>concavity_worst</th>\n",
       "      <th>points_worst</th>\n",
       "      <th>symmetry_worst</th>\n",
       "      <th>dimension_worst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>87139402</td>\n",
       "      <td>B</td>\n",
       "      <td>12.32</td>\n",
       "      <td>12.39</td>\n",
       "      <td>78.85</td>\n",
       "      <td>464.1</td>\n",
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       "      <td>0.06981</td>\n",
       "      <td>0.03987</td>\n",
       "      <td>0.03700</td>\n",
       "      <td>...</td>\n",
       "      <td>13.50</td>\n",
       "      <td>15.64</td>\n",
       "      <td>86.97</td>\n",
       "      <td>549.1</td>\n",
       "      <td>0.1385</td>\n",
       "      <td>0.1266</td>\n",
       "      <td>0.12420</td>\n",
       "      <td>0.09391</td>\n",
       "      <td>0.2827</td>\n",
       "      <td>0.06771</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8910251</td>\n",
       "      <td>B</td>\n",
       "      <td>10.60</td>\n",
       "      <td>18.95</td>\n",
       "      <td>69.28</td>\n",
       "      <td>346.4</td>\n",
       "      <td>0.09688</td>\n",
       "      <td>0.11470</td>\n",
       "      <td>0.06387</td>\n",
       "      <td>0.02642</td>\n",
       "      <td>...</td>\n",
       "      <td>11.88</td>\n",
       "      <td>22.94</td>\n",
       "      <td>78.28</td>\n",
       "      <td>424.8</td>\n",
       "      <td>0.1213</td>\n",
       "      <td>0.2515</td>\n",
       "      <td>0.19160</td>\n",
       "      <td>0.07926</td>\n",
       "      <td>0.2940</td>\n",
       "      <td>0.07587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>905520</td>\n",
       "      <td>B</td>\n",
       "      <td>11.04</td>\n",
       "      <td>16.83</td>\n",
       "      <td>70.92</td>\n",
       "      <td>373.2</td>\n",
       "      <td>0.10770</td>\n",
       "      <td>0.07804</td>\n",
       "      <td>0.03046</td>\n",
       "      <td>0.02480</td>\n",
       "      <td>...</td>\n",
       "      <td>12.41</td>\n",
       "      <td>26.44</td>\n",
       "      <td>79.93</td>\n",
       "      <td>471.4</td>\n",
       "      <td>0.1369</td>\n",
       "      <td>0.1482</td>\n",
       "      <td>0.10670</td>\n",
       "      <td>0.07431</td>\n",
       "      <td>0.2998</td>\n",
       "      <td>0.07881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>868871</td>\n",
       "      <td>B</td>\n",
       "      <td>11.28</td>\n",
       "      <td>13.39</td>\n",
       "      <td>73.00</td>\n",
       "      <td>384.8</td>\n",
       "      <td>0.11640</td>\n",
       "      <td>0.11360</td>\n",
       "      <td>0.04635</td>\n",
       "      <td>0.04796</td>\n",
       "      <td>...</td>\n",
       "      <td>11.92</td>\n",
       "      <td>15.77</td>\n",
       "      <td>76.53</td>\n",
       "      <td>434.0</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>0.1822</td>\n",
       "      <td>0.08669</td>\n",
       "      <td>0.08611</td>\n",
       "      <td>0.2102</td>\n",
       "      <td>0.06784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9012568</td>\n",
       "      <td>B</td>\n",
       "      <td>15.19</td>\n",
       "      <td>13.21</td>\n",
       "      <td>97.65</td>\n",
       "      <td>711.8</td>\n",
       "      <td>0.07963</td>\n",
       "      <td>0.06934</td>\n",
       "      <td>0.03393</td>\n",
       "      <td>0.02657</td>\n",
       "      <td>...</td>\n",
       "      <td>16.20</td>\n",
       "      <td>15.73</td>\n",
       "      <td>104.50</td>\n",
       "      <td>819.1</td>\n",
       "      <td>0.1126</td>\n",
       "      <td>0.1737</td>\n",
       "      <td>0.13620</td>\n",
       "      <td>0.08178</td>\n",
       "      <td>0.2487</td>\n",
       "      <td>0.06766</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id diagnosis  radius_mean  texture_mean  perimeter_mean  area_mean  \\\n",
       "0  87139402         B        12.32         12.39           78.85      464.1   \n",
       "1   8910251         B        10.60         18.95           69.28      346.4   \n",
       "2    905520         B        11.04         16.83           70.92      373.2   \n",
       "3    868871         B        11.28         13.39           73.00      384.8   \n",
       "4   9012568         B        15.19         13.21           97.65      711.8   \n",
       "\n",
       "   smoothness_mean  compactness_mean  concavity_mean  points_mean  \\\n",
       "0          0.10280           0.06981         0.03987      0.03700   \n",
       "1          0.09688           0.11470         0.06387      0.02642   \n",
       "2          0.10770           0.07804         0.03046      0.02480   \n",
       "3          0.11640           0.11360         0.04635      0.04796   \n",
       "4          0.07963           0.06934         0.03393      0.02657   \n",
       "\n",
       "        ...         radius_worst  texture_worst  perimeter_worst  area_worst  \\\n",
       "0       ...                13.50          15.64            86.97       549.1   \n",
       "1       ...                11.88          22.94            78.28       424.8   \n",
       "2       ...                12.41          26.44            79.93       471.4   \n",
       "3       ...                11.92          15.77            76.53       434.0   \n",
       "4       ...                16.20          15.73           104.50       819.1   \n",
       "\n",
       "   smoothness_worst  compactness_worst  concavity_worst  points_worst  \\\n",
       "0            0.1385             0.1266          0.12420       0.09391   \n",
       "1            0.1213             0.2515          0.19160       0.07926   \n",
       "2            0.1369             0.1482          0.10670       0.07431   \n",
       "3            0.1367             0.1822          0.08669       0.08611   \n",
       "4            0.1126             0.1737          0.13620       0.08178   \n",
       "\n",
       "   symmetry_worst  dimension_worst  \n",
       "0          0.2827          0.06771  \n",
       "1          0.2940          0.07587  \n",
       "2          0.2998          0.07881  \n",
       "3          0.2102          0.06784  \n",
       "4          0.2487          0.06766  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 276,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "del data[\"id\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>diagnosis</th>\n",
       "      <th>radius_mean</th>\n",
       "      <th>texture_mean</th>\n",
       "      <th>perimeter_mean</th>\n",
       "      <th>area_mean</th>\n",
       "      <th>smoothness_mean</th>\n",
       "      <th>compactness_mean</th>\n",
       "      <th>concavity_mean</th>\n",
       "      <th>points_mean</th>\n",
       "      <th>symmetry_mean</th>\n",
       "      <th>...</th>\n",
       "      <th>radius_worst</th>\n",
       "      <th>texture_worst</th>\n",
       "      <th>perimeter_worst</th>\n",
       "      <th>area_worst</th>\n",
       "      <th>smoothness_worst</th>\n",
       "      <th>compactness_worst</th>\n",
       "      <th>concavity_worst</th>\n",
       "      <th>points_worst</th>\n",
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       "      <th>0</th>\n",
       "      <td>B</td>\n",
       "      <td>12.32</td>\n",
       "      <td>12.39</td>\n",
       "      <td>78.85</td>\n",
       "      <td>464.1</td>\n",
       "      <td>0.10280</td>\n",
       "      <td>0.06981</td>\n",
       "      <td>0.03987</td>\n",
       "      <td>0.03700</td>\n",
       "      <td>0.1959</td>\n",
       "      <td>...</td>\n",
       "      <td>13.50</td>\n",
       "      <td>15.64</td>\n",
       "      <td>86.97</td>\n",
       "      <td>549.1</td>\n",
       "      <td>0.1385</td>\n",
       "      <td>0.1266</td>\n",
       "      <td>0.12420</td>\n",
       "      <td>0.09391</td>\n",
       "      <td>0.2827</td>\n",
       "      <td>0.06771</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>10.60</td>\n",
       "      <td>18.95</td>\n",
       "      <td>69.28</td>\n",
       "      <td>346.4</td>\n",
       "      <td>0.09688</td>\n",
       "      <td>0.11470</td>\n",
       "      <td>0.06387</td>\n",
       "      <td>0.02642</td>\n",
       "      <td>0.1922</td>\n",
       "      <td>...</td>\n",
       "      <td>11.88</td>\n",
       "      <td>22.94</td>\n",
       "      <td>78.28</td>\n",
       "      <td>424.8</td>\n",
       "      <td>0.1213</td>\n",
       "      <td>0.2515</td>\n",
       "      <td>0.19160</td>\n",
       "      <td>0.07926</td>\n",
       "      <td>0.2940</td>\n",
       "      <td>0.07587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B</td>\n",
       "      <td>11.04</td>\n",
       "      <td>16.83</td>\n",
       "      <td>70.92</td>\n",
       "      <td>373.2</td>\n",
       "      <td>0.10770</td>\n",
       "      <td>0.07804</td>\n",
       "      <td>0.03046</td>\n",
       "      <td>0.02480</td>\n",
       "      <td>0.1714</td>\n",
       "      <td>...</td>\n",
       "      <td>12.41</td>\n",
       "      <td>26.44</td>\n",
       "      <td>79.93</td>\n",
       "      <td>471.4</td>\n",
       "      <td>0.1369</td>\n",
       "      <td>0.1482</td>\n",
       "      <td>0.10670</td>\n",
       "      <td>0.07431</td>\n",
       "      <td>0.2998</td>\n",
       "      <td>0.07881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B</td>\n",
       "      <td>11.28</td>\n",
       "      <td>13.39</td>\n",
       "      <td>73.00</td>\n",
       "      <td>384.8</td>\n",
       "      <td>0.11640</td>\n",
       "      <td>0.11360</td>\n",
       "      <td>0.04635</td>\n",
       "      <td>0.04796</td>\n",
       "      <td>0.1771</td>\n",
       "      <td>...</td>\n",
       "      <td>11.92</td>\n",
       "      <td>15.77</td>\n",
       "      <td>76.53</td>\n",
       "      <td>434.0</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>0.1822</td>\n",
       "      <td>0.08669</td>\n",
       "      <td>0.08611</td>\n",
       "      <td>0.2102</td>\n",
       "      <td>0.06784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>15.19</td>\n",
       "      <td>13.21</td>\n",
       "      <td>97.65</td>\n",
       "      <td>711.8</td>\n",
       "      <td>0.07963</td>\n",
       "      <td>0.06934</td>\n",
       "      <td>0.03393</td>\n",
       "      <td>0.02657</td>\n",
       "      <td>0.1721</td>\n",
       "      <td>...</td>\n",
       "      <td>16.20</td>\n",
       "      <td>15.73</td>\n",
       "      <td>104.50</td>\n",
       "      <td>819.1</td>\n",
       "      <td>0.1126</td>\n",
       "      <td>0.1737</td>\n",
       "      <td>0.13620</td>\n",
       "      <td>0.08178</td>\n",
       "      <td>0.2487</td>\n",
       "      <td>0.06766</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  diagnosis  radius_mean  texture_mean  perimeter_mean  area_mean  \\\n",
       "0         B        12.32         12.39           78.85      464.1   \n",
       "1         B        10.60         18.95           69.28      346.4   \n",
       "2         B        11.04         16.83           70.92      373.2   \n",
       "3         B        11.28         13.39           73.00      384.8   \n",
       "4         B        15.19         13.21           97.65      711.8   \n",
       "\n",
       "   smoothness_mean  compactness_mean  concavity_mean  points_mean  \\\n",
       "0          0.10280           0.06981         0.03987      0.03700   \n",
       "1          0.09688           0.11470         0.06387      0.02642   \n",
       "2          0.10770           0.07804         0.03046      0.02480   \n",
       "3          0.11640           0.11360         0.04635      0.04796   \n",
       "4          0.07963           0.06934         0.03393      0.02657   \n",
       "\n",
       "   symmetry_mean       ...         radius_worst  texture_worst  \\\n",
       "0         0.1959       ...                13.50          15.64   \n",
       "1         0.1922       ...                11.88          22.94   \n",
       "2         0.1714       ...                12.41          26.44   \n",
       "3         0.1771       ...                11.92          15.77   \n",
       "4         0.1721       ...                16.20          15.73   \n",
       "\n",
       "   perimeter_worst  area_worst  smoothness_worst  compactness_worst  \\\n",
       "0            86.97       549.1            0.1385             0.1266   \n",
       "1            78.28       424.8            0.1213             0.2515   \n",
       "2            79.93       471.4            0.1369             0.1482   \n",
       "3            76.53       434.0            0.1367             0.1822   \n",
       "4           104.50       819.1            0.1126             0.1737   \n",
       "\n",
       "   concavity_worst  points_worst  symmetry_worst  dimension_worst  \n",
       "0          0.12420       0.09391          0.2827          0.06771  \n",
       "1          0.19160       0.07926          0.2940          0.07587  \n",
       "2          0.10670       0.07431          0.2998          0.07881  \n",
       "3          0.08669       0.08611          0.2102          0.06784  \n",
       "4          0.13620       0.08178          0.2487          0.06766  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data1 = data.iloc[:, 1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>radius_mean</th>\n",
       "      <th>texture_mean</th>\n",
       "      <th>perimeter_mean</th>\n",
       "      <th>area_mean</th>\n",
       "      <th>smoothness_mean</th>\n",
       "      <th>compactness_mean</th>\n",
       "      <th>concavity_mean</th>\n",
       "      <th>points_mean</th>\n",
       "      <th>symmetry_mean</th>\n",
       "      <th>dimension_mean</th>\n",
       "      <th>...</th>\n",
       "      <th>radius_worst</th>\n",
       "      <th>texture_worst</th>\n",
       "      <th>perimeter_worst</th>\n",
       "      <th>area_worst</th>\n",
       "      <th>smoothness_worst</th>\n",
       "      <th>compactness_worst</th>\n",
       "      <th>concavity_worst</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>12.32</td>\n",
       "      <td>12.39</td>\n",
       "      <td>78.85</td>\n",
       "      <td>464.1</td>\n",
       "      <td>0.10280</td>\n",
       "      <td>0.06981</td>\n",
       "      <td>0.03987</td>\n",
       "      <td>0.03700</td>\n",
       "      <td>0.1959</td>\n",
       "      <td>0.05955</td>\n",
       "      <td>...</td>\n",
       "      <td>13.50</td>\n",
       "      <td>15.64</td>\n",
       "      <td>86.97</td>\n",
       "      <td>549.1</td>\n",
       "      <td>0.1385</td>\n",
       "      <td>0.1266</td>\n",
       "      <td>0.12420</td>\n",
       "      <td>0.09391</td>\n",
       "      <td>0.2827</td>\n",
       "      <td>0.06771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.60</td>\n",
       "      <td>18.95</td>\n",
       "      <td>69.28</td>\n",
       "      <td>346.4</td>\n",
       "      <td>0.09688</td>\n",
       "      <td>0.11470</td>\n",
       "      <td>0.06387</td>\n",
       "      <td>0.02642</td>\n",
       "      <td>0.1922</td>\n",
       "      <td>0.06491</td>\n",
       "      <td>...</td>\n",
       "      <td>11.88</td>\n",
       "      <td>22.94</td>\n",
       "      <td>78.28</td>\n",
       "      <td>424.8</td>\n",
       "      <td>0.1213</td>\n",
       "      <td>0.2515</td>\n",
       "      <td>0.19160</td>\n",
       "      <td>0.07926</td>\n",
       "      <td>0.2940</td>\n",
       "      <td>0.07587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11.04</td>\n",
       "      <td>16.83</td>\n",
       "      <td>70.92</td>\n",
       "      <td>373.2</td>\n",
       "      <td>0.10770</td>\n",
       "      <td>0.07804</td>\n",
       "      <td>0.03046</td>\n",
       "      <td>0.02480</td>\n",
       "      <td>0.1714</td>\n",
       "      <td>0.06340</td>\n",
       "      <td>...</td>\n",
       "      <td>12.41</td>\n",
       "      <td>26.44</td>\n",
       "      <td>79.93</td>\n",
       "      <td>471.4</td>\n",
       "      <td>0.1369</td>\n",
       "      <td>0.1482</td>\n",
       "      <td>0.10670</td>\n",
       "      <td>0.07431</td>\n",
       "      <td>0.2998</td>\n",
       "      <td>0.07881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.28</td>\n",
       "      <td>13.39</td>\n",
       "      <td>73.00</td>\n",
       "      <td>384.8</td>\n",
       "      <td>0.11640</td>\n",
       "      <td>0.11360</td>\n",
       "      <td>0.04635</td>\n",
       "      <td>0.04796</td>\n",
       "      <td>0.1771</td>\n",
       "      <td>0.06072</td>\n",
       "      <td>...</td>\n",
       "      <td>11.92</td>\n",
       "      <td>15.77</td>\n",
       "      <td>76.53</td>\n",
       "      <td>434.0</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>0.1822</td>\n",
       "      <td>0.08669</td>\n",
       "      <td>0.08611</td>\n",
       "      <td>0.2102</td>\n",
       "      <td>0.06784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.19</td>\n",
       "      <td>13.21</td>\n",
       "      <td>97.65</td>\n",
       "      <td>711.8</td>\n",
       "      <td>0.07963</td>\n",
       "      <td>0.06934</td>\n",
       "      <td>0.03393</td>\n",
       "      <td>0.02657</td>\n",
       "      <td>0.1721</td>\n",
       "      <td>0.05544</td>\n",
       "      <td>...</td>\n",
       "      <td>16.20</td>\n",
       "      <td>15.73</td>\n",
       "      <td>104.50</td>\n",
       "      <td>819.1</td>\n",
       "      <td>0.1126</td>\n",
       "      <td>0.1737</td>\n",
       "      <td>0.13620</td>\n",
       "      <td>0.08178</td>\n",
       "      <td>0.2487</td>\n",
       "      <td>0.06766</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   radius_mean  texture_mean  perimeter_mean  area_mean  smoothness_mean  \\\n",
       "0        12.32         12.39           78.85      464.1          0.10280   \n",
       "1        10.60         18.95           69.28      346.4          0.09688   \n",
       "2        11.04         16.83           70.92      373.2          0.10770   \n",
       "3        11.28         13.39           73.00      384.8          0.11640   \n",
       "4        15.19         13.21           97.65      711.8          0.07963   \n",
       "\n",
       "   compactness_mean  concavity_mean  points_mean  symmetry_mean  \\\n",
       "0           0.06981         0.03987      0.03700         0.1959   \n",
       "1           0.11470         0.06387      0.02642         0.1922   \n",
       "2           0.07804         0.03046      0.02480         0.1714   \n",
       "3           0.11360         0.04635      0.04796         0.1771   \n",
       "4           0.06934         0.03393      0.02657         0.1721   \n",
       "\n",
       "   dimension_mean       ...         radius_worst  texture_worst  \\\n",
       "0         0.05955       ...                13.50          15.64   \n",
       "1         0.06491       ...                11.88          22.94   \n",
       "2         0.06340       ...                12.41          26.44   \n",
       "3         0.06072       ...                11.92          15.77   \n",
       "4         0.05544       ...                16.20          15.73   \n",
       "\n",
       "   perimeter_worst  area_worst  smoothness_worst  compactness_worst  \\\n",
       "0            86.97       549.1            0.1385             0.1266   \n",
       "1            78.28       424.8            0.1213             0.2515   \n",
       "2            79.93       471.4            0.1369             0.1482   \n",
       "3            76.53       434.0            0.1367             0.1822   \n",
       "4           104.50       819.1            0.1126             0.1737   \n",
       "\n",
       "   concavity_worst  points_worst  symmetry_worst  dimension_worst  \n",
       "0          0.12420       0.09391          0.2827          0.06771  \n",
       "1          0.19160       0.07926          0.2940          0.07587  \n",
       "2          0.10670       0.07431          0.2998          0.07881  \n",
       "3          0.08669       0.08611          0.2102          0.06784  \n",
       "4          0.13620       0.08178          0.2487          0.06766  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "min_max_scaler = preprocessing.MinMaxScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_scaled = min_max_scaler.fit_transform(data1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data2 = pd.DataFrame(data_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.271043</td>\n",
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       "      <td>0.123260</td>\n",
       "      <td>0.330303</td>\n",
       "      <td>0.283067</td>\n",
       "      <td>...</td>\n",
       "      <td>0.159374</td>\n",
       "      <td>0.384328</td>\n",
       "      <td>0.147019</td>\n",
       "      <td>0.070340</td>\n",
       "      <td>0.434062</td>\n",
       "      <td>0.117307</td>\n",
       "      <td>0.085224</td>\n",
       "      <td>0.255361</td>\n",
       "      <td>0.282476</td>\n",
       "      <td>0.155910</td>\n",
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       "      <td>0.124450</td>\n",
       "      <td>0.201852</td>\n",
       "      <td>0.102354</td>\n",
       "      <td>0.575697</td>\n",
       "      <td>0.289001</td>\n",
       "      <td>0.108599</td>\n",
       "      <td>0.238370</td>\n",
       "      <td>0.359091</td>\n",
       "      <td>0.226622</td>\n",
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       "      <td>0.099947</td>\n",
       "      <td>0.130086</td>\n",
       "      <td>0.061148</td>\n",
       "      <td>0.432741</td>\n",
       "      <td>0.150294</td>\n",
       "      <td>0.069241</td>\n",
       "      <td>0.295911</td>\n",
       "      <td>0.105855</td>\n",
       "      <td>0.083956</td>\n",
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       "      <th>4</th>\n",
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       "      <td>0.118363</td>\n",
       "      <td>0.372193</td>\n",
       "      <td>0.241060</td>\n",
       "      <td>0.243748</td>\n",
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       "      <td>0.132058</td>\n",
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       "         0         1         2         3         4         5         6   \\\n",
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       "\n",
       "         7         8         9     ...           20        21        22  \\\n",
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       "1  0.131312  0.435354  0.314869    ...     0.140519  0.291045  0.138802   \n",
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       "4  0.132058  0.333838  0.115417    ...     0.294201  0.098881  0.269386   \n",
       "\n",
       "         23        24        25        26        27        28        29  \n",
       "0  0.089437  0.444628  0.096351  0.099201  0.322715  0.248768  0.083104  \n",
       "1  0.058887  0.331044  0.217530  0.153035  0.272371  0.271043  0.136626  \n",
       "2  0.070340  0.434062  0.117307  0.085224  0.255361  0.282476  0.155910  \n",
       "3  0.061148  0.432741  0.150294  0.069241  0.295911  0.105855  0.083956  \n",
       "4  0.155795  0.273592  0.142048  0.108786  0.281031  0.181747  0.082776  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data2[30] = data[\"diagnosis\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.497156</td>\n",
       "      <td>0.179928</td>\n",
       "      <td>0.071368</td>\n",
       "      <td>0.123260</td>\n",
       "      <td>0.330303</td>\n",
       "      <td>0.283067</td>\n",
       "      <td>...</td>\n",
       "      <td>0.384328</td>\n",
       "      <td>0.147019</td>\n",
       "      <td>0.070340</td>\n",
       "      <td>0.434062</td>\n",
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       "      <td>0.255361</td>\n",
       "      <td>0.282476</td>\n",
       "      <td>0.155910</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.203464</td>\n",
       "      <td>0.124450</td>\n",
       "      <td>0.201852</td>\n",
       "      <td>0.102354</td>\n",
       "      <td>0.575697</td>\n",
       "      <td>0.289001</td>\n",
       "      <td>0.108599</td>\n",
       "      <td>0.238370</td>\n",
       "      <td>0.359091</td>\n",
       "      <td>0.226622</td>\n",
       "      <td>...</td>\n",
       "      <td>0.099947</td>\n",
       "      <td>0.130086</td>\n",
       "      <td>0.061148</td>\n",
       "      <td>0.432741</td>\n",
       "      <td>0.150294</td>\n",
       "      <td>0.069241</td>\n",
       "      <td>0.295911</td>\n",
       "      <td>0.105855</td>\n",
       "      <td>0.083956</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.388518</td>\n",
       "      <td>0.118363</td>\n",
       "      <td>0.372193</td>\n",
       "      <td>0.241060</td>\n",
       "      <td>0.243748</td>\n",
       "      <td>0.153242</td>\n",
       "      <td>0.079499</td>\n",
       "      <td>0.132058</td>\n",
       "      <td>0.333838</td>\n",
       "      <td>0.115417</td>\n",
       "      <td>...</td>\n",
       "      <td>0.098881</td>\n",
       "      <td>0.269386</td>\n",
       "      <td>0.155795</td>\n",
       "      <td>0.273592</td>\n",
       "      <td>0.142048</td>\n",
       "      <td>0.108786</td>\n",
       "      <td>0.281031</td>\n",
       "      <td>0.181747</td>\n",
       "      <td>0.082776</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
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       "         0         1         2         3         4         5         6   \\\n",
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       "1  0.171281  0.312479  0.176145  0.086066  0.399476  0.292375  0.149649   \n",
       "2  0.192106  0.240785  0.187478  0.097434  0.497156  0.179928  0.071368   \n",
       "3  0.203464  0.124450  0.201852  0.102354  0.575697  0.289001  0.108599   \n",
       "4  0.388518  0.118363  0.372193  0.241060  0.243748  0.153242  0.079499   \n",
       "\n",
       "         7         8         9  ...        21        22        23        24  \\\n",
       "0  0.183897  0.454040  0.201980 ...  0.096482  0.182081  0.089437  0.444628   \n",
       "1  0.131312  0.435354  0.314869 ...  0.291045  0.138802  0.058887  0.331044   \n",
       "2  0.123260  0.330303  0.283067 ...  0.384328  0.147019  0.070340  0.434062   \n",
       "3  0.238370  0.359091  0.226622 ...  0.099947  0.130086  0.061148  0.432741   \n",
       "4  0.132058  0.333838  0.115417 ...  0.098881  0.269386  0.155795  0.273592   \n",
       "\n",
       "         25        26        27        28        29  30  \n",
       "0  0.096351  0.099201  0.322715  0.248768  0.083104   B  \n",
       "1  0.217530  0.153035  0.272371  0.271043  0.136626   B  \n",
       "2  0.117307  0.085224  0.255361  0.282476  0.155910   B  \n",
       "3  0.150294  0.069241  0.295911  0.105855  0.083956   B  \n",
       "4  0.142048  0.108786  0.281031  0.181747  0.082776   B  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "label_encoder = preprocessing.LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "label = label_encoder.fit_transform(data2[30])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [
    {
     "data": {
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  {
   "cell_type": "code",
   "execution_count": 290,
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   "source": [
    "data2[30] = label"
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  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
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       "[5 rows x 31 columns]"
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     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "data2.head()"
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  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_x, test_x, train_y, test_y = train_test_split(data2.iloc[:, :-1],data2[30], test_size = 0.2)"
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  {
   "cell_type": "code",
   "execution_count": 293,
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   "outputs": [
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       "      <td>0.269386</td>\n",
       "      <td>0.155795</td>\n",
       "      <td>0.273592</td>\n",
       "      <td>0.142048</td>\n",
       "      <td>0.108786</td>\n",
       "      <td>0.281031</td>\n",
       "      <td>0.181747</td>\n",
       "      <td>0.082776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.279663</td>\n",
       "      <td>0.115320</td>\n",
       "      <td>0.263285</td>\n",
       "      <td>0.157964</td>\n",
       "      <td>0.152749</td>\n",
       "      <td>0.054935</td>\n",
       "      <td>0.052952</td>\n",
       "      <td>0.058201</td>\n",
       "      <td>0.139899</td>\n",
       "      <td>0.123210</td>\n",
       "      <td>...</td>\n",
       "      <td>0.202419</td>\n",
       "      <td>0.093817</td>\n",
       "      <td>0.184222</td>\n",
       "      <td>0.096294</td>\n",
       "      <td>0.165027</td>\n",
       "      <td>0.084806</td>\n",
       "      <td>0.094728</td>\n",
       "      <td>0.184399</td>\n",
       "      <td>0.146659</td>\n",
       "      <td>0.092549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535</th>\n",
       "      <td>0.276823</td>\n",
       "      <td>0.203585</td>\n",
       "      <td>0.270196</td>\n",
       "      <td>0.154146</td>\n",
       "      <td>0.340977</td>\n",
       "      <td>0.194191</td>\n",
       "      <td>0.136715</td>\n",
       "      <td>0.152982</td>\n",
       "      <td>0.325758</td>\n",
       "      <td>0.193134</td>\n",
       "      <td>...</td>\n",
       "      <td>0.219139</td>\n",
       "      <td>0.195362</td>\n",
       "      <td>0.213208</td>\n",
       "      <td>0.103372</td>\n",
       "      <td>0.405666</td>\n",
       "      <td>0.226747</td>\n",
       "      <td>0.277636</td>\n",
       "      <td>0.336186</td>\n",
       "      <td>0.284053</td>\n",
       "      <td>0.150728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>0.523877</td>\n",
       "      <td>0.217788</td>\n",
       "      <td>0.528022</td>\n",
       "      <td>0.365854</td>\n",
       "      <td>0.486323</td>\n",
       "      <td>0.598798</td>\n",
       "      <td>0.394564</td>\n",
       "      <td>0.536779</td>\n",
       "      <td>0.551515</td>\n",
       "      <td>0.353201</td>\n",
       "      <td>...</td>\n",
       "      <td>0.514408</td>\n",
       "      <td>0.183635</td>\n",
       "      <td>0.496489</td>\n",
       "      <td>0.350177</td>\n",
       "      <td>0.506042</td>\n",
       "      <td>0.520137</td>\n",
       "      <td>0.302396</td>\n",
       "      <td>0.722337</td>\n",
       "      <td>0.430909</td>\n",
       "      <td>0.365735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>0.138341</td>\n",
       "      <td>0.282381</td>\n",
       "      <td>0.143805</td>\n",
       "      <td>0.067402</td>\n",
       "      <td>0.400469</td>\n",
       "      <td>0.337464</td>\n",
       "      <td>0.306232</td>\n",
       "      <td>0.184692</td>\n",
       "      <td>0.307576</td>\n",
       "      <td>0.657119</td>\n",
       "      <td>...</td>\n",
       "      <td>0.118463</td>\n",
       "      <td>0.329691</td>\n",
       "      <td>0.112854</td>\n",
       "      <td>0.050383</td>\n",
       "      <td>0.389157</td>\n",
       "      <td>0.259734</td>\n",
       "      <td>0.278435</td>\n",
       "      <td>0.340550</td>\n",
       "      <td>0.206781</td>\n",
       "      <td>0.401154</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0         1         2         3         4         5         6   \\\n",
       "4    0.388518  0.118363  0.372193  0.241060  0.243748  0.153242  0.079499   \n",
       "85   0.279663  0.115320  0.263285  0.157964  0.152749  0.054935  0.052952   \n",
       "535  0.276823  0.203585  0.270196  0.154146  0.340977  0.194191  0.136715   \n",
       "280  0.523877  0.217788  0.528022  0.365854  0.486323  0.598798  0.394564   \n",
       "483  0.138341  0.282381  0.143805  0.067402  0.400469  0.337464  0.306232   \n",
       "\n",
       "           7         8         9     ...           20        21        22  \\\n",
       "4    0.132058  0.333838  0.115417    ...     0.294201  0.098881  0.269386   \n",
       "85   0.058201  0.139899  0.123210    ...     0.202419  0.093817  0.184222   \n",
       "535  0.152982  0.325758  0.193134    ...     0.219139  0.195362  0.213208   \n",
       "280  0.536779  0.551515  0.353201    ...     0.514408  0.183635  0.496489   \n",
       "483  0.184692  0.307576  0.657119    ...     0.118463  0.329691  0.112854   \n",
       "\n",
       "           23        24        25        26        27        28        29  \n",
       "4    0.155795  0.273592  0.142048  0.108786  0.281031  0.181747  0.082776  \n",
       "85   0.096294  0.165027  0.084806  0.094728  0.184399  0.146659  0.092549  \n",
       "535  0.103372  0.405666  0.226747  0.277636  0.336186  0.284053  0.150728  \n",
       "280  0.350177  0.506042  0.520137  0.302396  0.722337  0.430909  0.365735  \n",
       "483  0.050383  0.389157  0.259734  0.278435  0.340550  0.206781  0.401154  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 293,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4      0\n",
       "85     0\n",
       "535    0\n",
       "280    1\n",
       "483    0\n",
       "Name: 30, dtype: int64"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn2 = knn(n_neighbors=21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=1, n_neighbors=21, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn2.fit(train_x, train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred = knn2.predict(test_x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[69,  8],\n",
       "       [ 1, 36]], dtype=int64)"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.confusion_matrix(y_pred, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.92105263157894735"
      ]
     },
     "execution_count": 299,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.accuracy_score(y_pred,test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(455, 30)"
      ]
     },
     "execution_count": 300,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of k = 1\n",
      "0.929824561404\n",
      "Accuracy of k = 2\n",
      "0.947368421053\n",
      "Accuracy of k = 3\n",
      "0.929824561404\n",
      "Accuracy of k = 4\n",
      "0.929824561404\n",
      "Accuracy of k = 5\n",
      "0.947368421053\n",
      "Accuracy of k = 6\n",
      "0.929824561404\n",
      "Accuracy of k = 7\n",
      "0.938596491228\n",
      "Accuracy of k = 8\n",
      "0.929824561404\n",
      "Accuracy of k = 9\n",
      "0.938596491228\n",
      "Accuracy of k = 10\n",
      "0.929824561404\n",
      "Accuracy of k = 11\n",
      "0.938596491228\n",
      "Accuracy of k = 12\n",
      "0.938596491228\n",
      "Accuracy of k = 13\n",
      "0.938596491228\n",
      "Accuracy of k = 14\n",
      "0.938596491228\n",
      "Accuracy of k = 15\n",
      "0.938596491228\n",
      "Accuracy of k = 16\n",
      "0.929824561404\n",
      "Accuracy of k = 17\n",
      "0.938596491228\n",
      "Accuracy of k = 18\n",
      "0.921052631579\n",
      "Accuracy of k = 19\n",
      "0.921052631579\n",
      "Accuracy of k = 20\n",
      "0.921052631579\n",
      "Accuracy of k = 21\n",
      "0.921052631579\n",
      "Accuracy of k = 22\n",
      "0.921052631579\n",
      "Accuracy of k = 23\n",
      "0.921052631579\n",
      "Accuracy of k = 24\n",
      "0.921052631579\n",
      "Accuracy of k = 25\n",
      "0.921052631579\n",
      "Accuracy of k = 26\n",
      "0.921052631579\n",
      "Accuracy of k = 27\n",
      "0.921052631579\n",
      "Accuracy of k = 28\n",
      "0.921052631579\n",
      "Accuracy of k = 29\n",
      "0.921052631579\n",
      "Accuracy of k = 30\n",
      "0.912280701754\n",
      "Accuracy of k = 31\n",
      "0.912280701754\n",
      "Accuracy of k = 32\n",
      "0.912280701754\n",
      "Accuracy of k = 33\n",
      "0.90350877193\n",
      "Accuracy of k = 34\n",
      "0.90350877193\n",
      "Accuracy of k = 35\n",
      "0.90350877193\n",
      "Accuracy of k = 36\n",
      "0.90350877193\n",
      "Accuracy of k = 37\n",
      "0.90350877193\n",
      "Accuracy of k = 38\n",
      "0.90350877193\n",
      "Accuracy of k = 39\n",
      "0.90350877193\n",
      "Accuracy of k = 40\n",
      "0.90350877193\n",
      "Accuracy of k = 41\n",
      "0.90350877193\n",
      "Accuracy of k = 42\n",
      "0.90350877193\n",
      "Accuracy of k = 43\n",
      "0.90350877193\n",
      "Accuracy of k = 44\n",
      "0.912280701754\n",
      "Accuracy of k = 45\n",
      "0.90350877193\n",
      "Accuracy of k = 46\n",
      "0.912280701754\n",
      "Accuracy of k = 47\n",
      "0.90350877193\n",
      "Accuracy of k = 48\n",
      "0.90350877193\n",
      "Accuracy of k = 49\n",
      "0.90350877193\n",
      "Accuracy of k = 50\n",
      "0.912280701754\n",
      "Accuracy of k = 51\n",
      "0.90350877193\n",
      "Accuracy of k = 52\n",
      "0.90350877193\n",
      "Accuracy of k = 53\n",
      "0.90350877193\n",
      "Accuracy of k = 54\n",
      "0.90350877193\n",
      "Accuracy of k = 55\n",
      "0.90350877193\n",
      "Accuracy of k = 56\n",
      "0.90350877193\n",
      "Accuracy of k = 57\n",
      "0.90350877193\n",
      "Accuracy of k = 58\n",
      "0.912280701754\n",
      "Accuracy of k = 59\n",
      "0.90350877193\n",
      "Accuracy of k = 60\n",
      "0.912280701754\n",
      "Accuracy of k = 61\n",
      "0.912280701754\n",
      "Accuracy of k = 62\n",
      "0.912280701754\n",
      "Accuracy of k = 63\n",
      "0.912280701754\n",
      "Accuracy of k = 64\n",
      "0.912280701754\n",
      "Accuracy of k = 65\n",
      "0.912280701754\n",
      "Accuracy of k = 66\n",
      "0.912280701754\n",
      "Accuracy of k = 67\n",
      "0.912280701754\n",
      "Accuracy of k = 68\n",
      "0.912280701754\n",
      "Accuracy of k = 69\n",
      "0.912280701754\n",
      "Accuracy of k = 70\n",
      "0.90350877193\n",
      "Accuracy of k = 71\n",
      "0.90350877193\n",
      "Accuracy of k = 72\n",
      "0.912280701754\n",
      "Accuracy of k = 73\n",
      "0.912280701754\n",
      "Accuracy of k = 74\n",
      "0.912280701754\n",
      "Accuracy of k = 75\n",
      "0.921052631579\n",
      "Accuracy of k = 76\n",
      "0.912280701754\n",
      "Accuracy of k = 77\n",
      "0.912280701754\n",
      "Accuracy of k = 78\n",
      "0.912280701754\n",
      "Accuracy of k = 79\n",
      "0.912280701754\n",
      "Accuracy of k = 80\n",
      "0.912280701754\n",
      "Accuracy of k = 81\n",
      "0.912280701754\n",
      "Accuracy of k = 82\n",
      "0.912280701754\n",
      "Accuracy of k = 83\n",
      "0.912280701754\n",
      "Accuracy of k = 84\n",
      "0.912280701754\n",
      "Accuracy of k = 85\n",
      "0.912280701754\n",
      "Accuracy of k = 86\n",
      "0.912280701754\n",
      "Accuracy of k = 87\n",
      "0.912280701754\n",
      "Accuracy of k = 88\n",
      "0.912280701754\n",
      "Accuracy of k = 89\n",
      "0.912280701754\n",
      "Accuracy of k = 90\n",
      "0.912280701754\n",
      "Accuracy of k = 91\n",
      "0.912280701754\n",
      "Accuracy of k = 92\n",
      "0.912280701754\n",
      "Accuracy of k = 93\n",
      "0.912280701754\n",
      "Accuracy of k = 94\n",
      "0.912280701754\n",
      "Accuracy of k = 95\n",
      "0.912280701754\n",
      "Accuracy of k = 96\n",
      "0.912280701754\n",
      "Accuracy of k = 97\n",
      "0.912280701754\n",
      "Accuracy of k = 98\n",
      "0.912280701754\n",
      "Accuracy of k = 99\n",
      "0.912280701754\n",
      "Accuracy of k = 100\n",
      "0.912280701754\n",
      "Accuracy of k = 101\n",
      "0.912280701754\n",
      "Accuracy of k = 102\n",
      "0.912280701754\n",
      "Accuracy of k = 103\n",
      "0.912280701754\n",
      "Accuracy of k = 104\n",
      "0.90350877193\n",
      "Accuracy of k = 105\n",
      "0.90350877193\n",
      "Accuracy of k = 106\n",
      "0.90350877193\n",
      "Accuracy of k = 107\n",
      "0.90350877193\n",
      "Accuracy of k = 108\n",
      "0.90350877193\n",
      "Accuracy of k = 109\n",
      "0.90350877193\n",
      "Accuracy of k = 110\n",
      "0.90350877193\n",
      "Accuracy of k = 111\n",
      "0.90350877193\n",
      "Accuracy of k = 112\n",
      "0.90350877193\n",
      "Accuracy of k = 113\n",
      "0.90350877193\n",
      "Accuracy of k = 114\n",
      "0.90350877193\n",
      "Accuracy of k = 115\n",
      "0.90350877193\n",
      "Accuracy of k = 116\n",
      "0.90350877193\n",
      "Accuracy of k = 117\n",
      "0.90350877193\n",
      "Accuracy of k = 118\n",
      "0.894736842105\n",
      "Accuracy of k = 119\n",
      "0.894736842105\n",
      "Accuracy of k = 120\n",
      "0.894736842105\n",
      "Accuracy of k = 121\n",
      "0.90350877193\n",
      "Accuracy of k = 122\n",
      "0.90350877193\n",
      "Accuracy of k = 123\n",
      "0.90350877193\n",
      "Accuracy of k = 124\n",
      "0.894736842105\n",
      "Accuracy of k = 125\n",
      "0.90350877193\n",
      "Accuracy of k = 126\n",
      "0.90350877193\n",
      "Accuracy of k = 127\n",
      "0.90350877193\n",
      "Accuracy of k = 128\n",
      "0.894736842105\n",
      "Accuracy of k = 129\n",
      "0.90350877193\n",
      "Accuracy of k = 130\n",
      "0.894736842105\n",
      "Accuracy of k = 131\n",
      "0.894736842105\n",
      "Accuracy of k = 132\n",
      "0.894736842105\n",
      "Accuracy of k = 133\n",
      "0.894736842105\n",
      "Accuracy of k = 134\n",
      "0.894736842105\n",
      "Accuracy of k = 135\n",
      "0.894736842105\n",
      "Accuracy of k = 136\n",
      "0.894736842105\n",
      "Accuracy of k = 137\n",
      "0.894736842105\n",
      "Accuracy of k = 138\n",
      "0.894736842105\n",
      "Accuracy of k = 139\n",
      "0.894736842105\n",
      "Accuracy of k = 140\n",
      "0.894736842105\n",
      "Accuracy of k = 141\n",
      "0.894736842105\n",
      "Accuracy of k = 142\n",
      "0.894736842105\n",
      "Accuracy of k = 143\n",
      "0.894736842105\n",
      "Accuracy of k = 144\n",
      "0.894736842105\n",
      "Accuracy of k = 145\n",
      "0.894736842105\n",
      "Accuracy of k = 146\n",
      "0.894736842105\n",
      "Accuracy of k = 147\n",
      "0.894736842105\n",
      "Accuracy of k = 148\n",
      "0.894736842105\n",
      "Accuracy of k = 149\n",
      "0.894736842105\n",
      "Accuracy of k = 150\n",
      "0.894736842105\n",
      "Accuracy of k = 151\n",
      "0.894736842105\n",
      "Accuracy of k = 152\n",
      "0.894736842105\n",
      "Accuracy of k = 153\n",
      "0.894736842105\n",
      "Accuracy of k = 154\n",
      "0.894736842105\n",
      "Accuracy of k = 155\n",
      "0.894736842105\n",
      "Accuracy of k = 156\n",
      "0.885964912281\n",
      "Accuracy of k = 157\n",
      "0.885964912281\n",
      "Accuracy of k = 158\n",
      "0.885964912281\n",
      "Accuracy of k = 159\n",
      "0.885964912281\n",
      "Accuracy of k = 160\n",
      "0.885964912281\n",
      "Accuracy of k = 161\n",
      "0.885964912281\n",
      "Accuracy of k = 162\n",
      "0.885964912281\n",
      "Accuracy of k = 163\n",
      "0.885964912281\n",
      "Accuracy of k = 164\n",
      "0.885964912281\n",
      "Accuracy of k = 165\n",
      "0.885964912281\n",
      "Accuracy of k = 166\n",
      "0.885964912281\n",
      "Accuracy of k = 167\n",
      "0.885964912281\n",
      "Accuracy of k = 168\n",
      "0.885964912281\n",
      "Accuracy of k = 169\n",
      "0.885964912281\n",
      "Accuracy of k = 170\n",
      "0.885964912281\n",
      "Accuracy of k = 171\n",
      "0.885964912281\n",
      "Accuracy of k = 172\n",
      "0.885964912281\n",
      "Accuracy of k = 173\n",
      "0.885964912281\n",
      "Accuracy of k = 174\n",
      "0.885964912281\n",
      "Accuracy of k = 175\n",
      "0.885964912281\n",
      "Accuracy of k = 176\n",
      "0.885964912281\n",
      "Accuracy of k = 177\n",
      "0.885964912281\n",
      "Accuracy of k = 178\n",
      "0.885964912281\n",
      "Accuracy of k = 179\n",
      "0.885964912281\n",
      "Accuracy of k = 180\n",
      "0.885964912281\n",
      "Accuracy of k = 181\n",
      "0.885964912281\n",
      "Accuracy of k = 182\n",
      "0.877192982456\n",
      "Accuracy of k = 183\n",
      "0.877192982456\n",
      "Accuracy of k = 184\n",
      "0.877192982456\n",
      "Accuracy of k = 185\n",
      "0.877192982456\n",
      "Accuracy of k = 186\n",
      "0.877192982456\n",
      "Accuracy of k = 187\n",
      "0.877192982456\n",
      "Accuracy of k = 188\n",
      "0.877192982456\n",
      "Accuracy of k = 189\n",
      "0.877192982456\n",
      "Accuracy of k = 190\n",
      "0.877192982456\n",
      "Accuracy of k = 191\n",
      "0.877192982456\n",
      "Accuracy of k = 192\n",
      "0.877192982456\n",
      "Accuracy of k = 193\n",
      "0.877192982456\n",
      "Accuracy of k = 194\n",
      "0.877192982456\n",
      "Accuracy of k = 195\n",
      "0.877192982456\n",
      "Accuracy of k = 196\n",
      "0.877192982456\n",
      "Accuracy of k = 197\n",
      "0.877192982456\n",
      "Accuracy of k = 198\n",
      "0.868421052632\n",
      "Accuracy of k = 199\n",
      "0.868421052632\n",
      "Accuracy of k = 200\n",
      "0.868421052632\n",
      "Accuracy of k = 201\n",
      "0.868421052632\n",
      "Accuracy of k = 202\n",
      "0.868421052632\n",
      "Accuracy of k = 203\n",
      "0.868421052632\n",
      "Accuracy of k = 204\n",
      "0.868421052632\n",
      "Accuracy of k = 205\n",
      "0.868421052632\n",
      "Accuracy of k = 206\n",
      "0.868421052632\n",
      "Accuracy of k = 207\n",
      "0.868421052632\n",
      "Accuracy of k = 208\n",
      "0.868421052632\n",
      "Accuracy of k = 209\n",
      "0.868421052632\n",
      "Accuracy of k = 210\n",
      "0.868421052632\n",
      "Accuracy of k = 211\n",
      "0.868421052632\n",
      "Accuracy of k = 212\n",
      "0.868421052632\n",
      "Accuracy of k = 213\n",
      "0.868421052632\n",
      "Accuracy of k = 214\n",
      "0.868421052632\n",
      "Accuracy of k = 215\n",
      "0.868421052632\n",
      "Accuracy of k = 216\n",
      "0.868421052632\n",
      "Accuracy of k = 217\n",
      "0.868421052632\n",
      "Accuracy of k = 218\n",
      "0.868421052632\n",
      "Accuracy of k = 219\n",
      "0.868421052632\n",
      "Accuracy of k = 220\n",
      "0.868421052632\n",
      "Accuracy of k = 221\n",
      "0.868421052632\n",
      "Accuracy of k = 222\n",
      "0.868421052632\n",
      "Accuracy of k = 223\n",
      "0.868421052632\n",
      "Accuracy of k = 224\n",
      "0.868421052632\n",
      "Accuracy of k = 225\n",
      "0.868421052632\n",
      "Accuracy of k = 226\n",
      "0.868421052632\n",
      "Accuracy of k = 227\n",
      "0.868421052632\n",
      "Accuracy of k = 228\n",
      "0.868421052632\n",
      "Accuracy of k = 229\n",
      "0.868421052632\n",
      "Accuracy of k = 230\n",
      "0.868421052632\n",
      "Accuracy of k = 231\n",
      "0.868421052632\n",
      "Accuracy of k = 232\n",
      "0.868421052632\n",
      "Accuracy of k = 233\n",
      "0.868421052632\n",
      "Accuracy of k = 234\n",
      "0.868421052632\n",
      "Accuracy of k = 235\n",
      "0.868421052632\n",
      "Accuracy of k = 236\n",
      "0.859649122807\n",
      "Accuracy of k = 237\n",
      "0.859649122807\n",
      "Accuracy of k = 238\n",
      "0.859649122807\n",
      "Accuracy of k = 239\n",
      "0.859649122807\n",
      "Accuracy of k = 240\n",
      "0.859649122807\n",
      "Accuracy of k = 241\n",
      "0.859649122807\n",
      "Accuracy of k = 242\n",
      "0.859649122807\n",
      "Accuracy of k = 243\n",
      "0.859649122807\n",
      "Accuracy of k = 244\n",
      "0.859649122807\n",
      "Accuracy of k = 245\n",
      "0.859649122807\n",
      "Accuracy of k = 246\n",
      "0.859649122807\n",
      "Accuracy of k = 247\n",
      "0.859649122807\n",
      "Accuracy of k = 248\n",
      "0.859649122807\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of k = 249\n",
      "0.859649122807\n",
      "Accuracy of k = 250\n",
      "0.859649122807\n",
      "Accuracy of k = 251\n",
      "0.859649122807\n",
      "Accuracy of k = 252\n",
      "0.859649122807\n",
      "Accuracy of k = 253\n",
      "0.859649122807\n",
      "Accuracy of k = 254\n",
      "0.859649122807\n",
      "Accuracy of k = 255\n",
      "0.859649122807\n",
      "Accuracy of k = 256\n",
      "0.859649122807\n",
      "Accuracy of k = 257\n",
      "0.859649122807\n",
      "Accuracy of k = 258\n",
      "0.859649122807\n",
      "Accuracy of k = 259\n",
      "0.859649122807\n",
      "Accuracy of k = 260\n",
      "0.859649122807\n",
      "Accuracy of k = 261\n",
      "0.859649122807\n",
      "Accuracy of k = 262\n",
      "0.859649122807\n",
      "Accuracy of k = 263\n",
      "0.859649122807\n",
      "Accuracy of k = 264\n",
      "0.859649122807\n",
      "Accuracy of k = 265\n",
      "0.859649122807\n",
      "Accuracy of k = 266\n",
      "0.859649122807\n",
      "Accuracy of k = 267\n",
      "0.859649122807\n",
      "Accuracy of k = 268\n",
      "0.842105263158\n",
      "Accuracy of k = 269\n",
      "0.842105263158\n",
      "Accuracy of k = 270\n",
      "0.842105263158\n",
      "Accuracy of k = 271\n",
      "0.842105263158\n",
      "Accuracy of k = 272\n",
      "0.842105263158\n",
      "Accuracy of k = 273\n",
      "0.842105263158\n",
      "Accuracy of k = 274\n",
      "0.842105263158\n",
      "Accuracy of k = 275\n",
      "0.842105263158\n",
      "Accuracy of k = 276\n",
      "0.842105263158\n",
      "Accuracy of k = 277\n",
      "0.842105263158\n",
      "Accuracy of k = 278\n",
      "0.842105263158\n",
      "Accuracy of k = 279\n",
      "0.842105263158\n",
      "Accuracy of k = 280\n",
      "0.842105263158\n",
      "Accuracy of k = 281\n",
      "0.842105263158\n",
      "Accuracy of k = 282\n",
      "0.833333333333\n",
      "Accuracy of k = 283\n",
      "0.833333333333\n",
      "Accuracy of k = 284\n",
      "0.833333333333\n",
      "Accuracy of k = 285\n",
      "0.833333333333\n",
      "Accuracy of k = 286\n",
      "0.833333333333\n",
      "Accuracy of k = 287\n",
      "0.833333333333\n",
      "Accuracy of k = 288\n",
      "0.824561403509\n",
      "Accuracy of k = 289\n",
      "0.824561403509\n",
      "Accuracy of k = 290\n",
      "0.815789473684\n",
      "Accuracy of k = 291\n",
      "0.815789473684\n",
      "Accuracy of k = 292\n",
      "0.80701754386\n",
      "Accuracy of k = 293\n",
      "0.815789473684\n",
      "Accuracy of k = 294\n",
      "0.80701754386\n",
      "Accuracy of k = 295\n",
      "0.80701754386\n",
      "Accuracy of k = 296\n",
      "0.789473684211\n",
      "Accuracy of k = 297\n",
      "0.798245614035\n",
      "Accuracy of k = 298\n",
      "0.789473684211\n",
      "Accuracy of k = 299\n",
      "0.798245614035\n",
      "Accuracy of k = 300\n",
      "0.771929824561\n",
      "Accuracy of k = 301\n",
      "0.789473684211\n",
      "Accuracy of k = 302\n",
      "0.754385964912\n",
      "Accuracy of k = 303\n",
      "0.754385964912\n",
      "Accuracy of k = 304\n",
      "0.754385964912\n",
      "Accuracy of k = 305\n",
      "0.754385964912\n",
      "Accuracy of k = 306\n",
      "0.736842105263\n",
      "Accuracy of k = 307\n",
      "0.736842105263\n",
      "Accuracy of k = 308\n",
      "0.728070175439\n",
      "Accuracy of k = 309\n",
      "0.728070175439\n",
      "Accuracy of k = 310\n",
      "0.728070175439\n",
      "Accuracy of k = 311\n",
      "0.728070175439\n",
      "Accuracy of k = 312\n",
      "0.728070175439\n",
      "Accuracy of k = 313\n",
      "0.728070175439\n",
      "Accuracy of k = 314\n",
      "0.710526315789\n",
      "Accuracy of k = 315\n",
      "0.710526315789\n",
      "Accuracy of k = 316\n",
      "0.710526315789\n",
      "Accuracy of k = 317\n",
      "0.710526315789\n",
      "Accuracy of k = 318\n",
      "0.701754385965\n",
      "Accuracy of k = 319\n",
      "0.701754385965\n",
      "Accuracy of k = 320\n",
      "0.675438596491\n",
      "Accuracy of k = 321\n",
      "0.684210526316\n",
      "Accuracy of k = 322\n",
      "0.675438596491\n",
      "Accuracy of k = 323\n",
      "0.675438596491\n",
      "Accuracy of k = 324\n",
      "0.666666666667\n",
      "Accuracy of k = 325\n",
      "0.666666666667\n",
      "Accuracy of k = 326\n",
      "0.657894736842\n",
      "Accuracy of k = 327\n",
      "0.657894736842\n",
      "Accuracy of k = 328\n",
      "0.640350877193\n",
      "Accuracy of k = 329\n",
      "0.640350877193\n",
      "Accuracy of k = 330\n",
      "0.622807017544\n",
      "Accuracy of k = 331\n",
      "0.622807017544\n",
      "Accuracy of k = 332\n",
      "0.622807017544\n",
      "Accuracy of k = 333\n",
      "0.622807017544\n",
      "Accuracy of k = 334\n",
      "0.614035087719\n",
      "Accuracy of k = 335\n",
      "0.614035087719\n",
      "Accuracy of k = 336\n",
      "0.614035087719\n",
      "Accuracy of k = 337\n",
      "0.614035087719\n",
      "Accuracy of k = 338\n",
      "0.614035087719\n",
      "Accuracy of k = 339\n",
      "0.614035087719\n",
      "Accuracy of k = 340\n",
      "0.614035087719\n",
      "Accuracy of k = 341\n",
      "0.614035087719\n",
      "Accuracy of k = 342\n",
      "0.614035087719\n",
      "Accuracy of k = 343\n",
      "0.614035087719\n",
      "Accuracy of k = 344\n",
      "0.614035087719\n",
      "Accuracy of k = 345\n",
      "0.614035087719\n",
      "Accuracy of k = 346\n",
      "0.614035087719\n",
      "Accuracy of k = 347\n",
      "0.614035087719\n",
      "Accuracy of k = 348\n",
      "0.614035087719\n",
      "Accuracy of k = 349\n",
      "0.614035087719\n",
      "Accuracy of k = 350\n",
      "0.614035087719\n",
      "Accuracy of k = 351\n",
      "0.614035087719\n",
      "Accuracy of k = 352\n",
      "0.614035087719\n",
      "Accuracy of k = 353\n",
      "0.614035087719\n",
      "Accuracy of k = 354\n",
      "0.614035087719\n",
      "Accuracy of k = 355\n",
      "0.614035087719\n",
      "Accuracy of k = 356\n",
      "0.614035087719\n",
      "Accuracy of k = 357\n",
      "0.614035087719\n",
      "Accuracy of k = 358\n",
      "0.614035087719\n",
      "Accuracy of k = 359\n",
      "0.614035087719\n",
      "Accuracy of k = 360\n",
      "0.614035087719\n",
      "Accuracy of k = 361\n",
      "0.614035087719\n",
      "Accuracy of k = 362\n",
      "0.614035087719\n",
      "Accuracy of k = 363\n",
      "0.614035087719\n",
      "Accuracy of k = 364\n",
      "0.614035087719\n",
      "Accuracy of k = 365\n",
      "0.614035087719\n",
      "Accuracy of k = 366\n",
      "0.614035087719\n",
      "Accuracy of k = 367\n",
      "0.614035087719\n",
      "Accuracy of k = 368\n",
      "0.614035087719\n",
      "Accuracy of k = 369\n",
      "0.614035087719\n",
      "Accuracy of k = 370\n",
      "0.614035087719\n",
      "Accuracy of k = 371\n",
      "0.614035087719\n",
      "Accuracy of k = 372\n",
      "0.614035087719\n",
      "Accuracy of k = 373\n",
      "0.614035087719\n",
      "Accuracy of k = 374\n",
      "0.614035087719\n",
      "Accuracy of k = 375\n",
      "0.614035087719\n",
      "Accuracy of k = 376\n",
      "0.614035087719\n",
      "Accuracy of k = 377\n",
      "0.614035087719\n",
      "Accuracy of k = 378\n",
      "0.614035087719\n",
      "Accuracy of k = 379\n",
      "0.614035087719\n",
      "Accuracy of k = 380\n",
      "0.614035087719\n",
      "Accuracy of k = 381\n",
      "0.614035087719\n",
      "Accuracy of k = 382\n",
      "0.614035087719\n",
      "Accuracy of k = 383\n",
      "0.614035087719\n",
      "Accuracy of k = 384\n",
      "0.614035087719\n",
      "Accuracy of k = 385\n",
      "0.614035087719\n",
      "Accuracy of k = 386\n",
      "0.614035087719\n",
      "Accuracy of k = 387\n",
      "0.614035087719\n",
      "Accuracy of k = 388\n",
      "0.614035087719\n",
      "Accuracy of k = 389\n",
      "0.614035087719\n",
      "Accuracy of k = 390\n",
      "0.614035087719\n",
      "Accuracy of k = 391\n",
      "0.614035087719\n",
      "Accuracy of k = 392\n",
      "0.614035087719\n",
      "Accuracy of k = 393\n",
      "0.614035087719\n",
      "Accuracy of k = 394\n",
      "0.614035087719\n",
      "Accuracy of k = 395\n",
      "0.614035087719\n",
      "Accuracy of k = 396\n",
      "0.614035087719\n",
      "Accuracy of k = 397\n",
      "0.614035087719\n",
      "Accuracy of k = 398\n",
      "0.614035087719\n",
      "Accuracy of k = 399\n",
      "0.614035087719\n",
      "Accuracy of k = 400\n",
      "0.614035087719\n",
      "Accuracy of k = 401\n",
      "0.614035087719\n",
      "Accuracy of k = 402\n",
      "0.614035087719\n",
      "Accuracy of k = 403\n",
      "0.614035087719\n",
      "Accuracy of k = 404\n",
      "0.614035087719\n",
      "Accuracy of k = 405\n",
      "0.614035087719\n",
      "Accuracy of k = 406\n",
      "0.614035087719\n",
      "Accuracy of k = 407\n",
      "0.614035087719\n",
      "Accuracy of k = 408\n",
      "0.614035087719\n",
      "Accuracy of k = 409\n",
      "0.614035087719\n",
      "Accuracy of k = 410\n",
      "0.614035087719\n",
      "Accuracy of k = 411\n",
      "0.614035087719\n",
      "Accuracy of k = 412\n",
      "0.614035087719\n",
      "Accuracy of k = 413\n",
      "0.614035087719\n",
      "Accuracy of k = 414\n",
      "0.614035087719\n",
      "Accuracy of k = 415\n",
      "0.614035087719\n",
      "Accuracy of k = 416\n",
      "0.614035087719\n",
      "Accuracy of k = 417\n",
      "0.614035087719\n",
      "Accuracy of k = 418\n",
      "0.614035087719\n",
      "Accuracy of k = 419\n",
      "0.614035087719\n",
      "Accuracy of k = 420\n",
      "0.614035087719\n",
      "Accuracy of k = 421\n",
      "0.614035087719\n",
      "Accuracy of k = 422\n",
      "0.614035087719\n",
      "Accuracy of k = 423\n",
      "0.614035087719\n",
      "Accuracy of k = 424\n",
      "0.614035087719\n",
      "Accuracy of k = 425\n",
      "0.614035087719\n",
      "Accuracy of k = 426\n",
      "0.614035087719\n",
      "Accuracy of k = 427\n",
      "0.614035087719\n",
      "Accuracy of k = 428\n",
      "0.614035087719\n",
      "Accuracy of k = 429\n",
      "0.614035087719\n",
      "Accuracy of k = 430\n",
      "0.614035087719\n",
      "Accuracy of k = 431\n",
      "0.614035087719\n",
      "Accuracy of k = 432\n",
      "0.614035087719\n",
      "Accuracy of k = 433\n",
      "0.614035087719\n",
      "Accuracy of k = 434\n",
      "0.614035087719\n",
      "Accuracy of k = 435\n",
      "0.614035087719\n",
      "Accuracy of k = 436\n",
      "0.614035087719\n",
      "Accuracy of k = 437\n",
      "0.614035087719\n",
      "Accuracy of k = 438\n",
      "0.614035087719\n",
      "Accuracy of k = 439\n",
      "0.614035087719\n",
      "Accuracy of k = 440\n",
      "0.614035087719\n",
      "Accuracy of k = 441\n",
      "0.614035087719\n",
      "Accuracy of k = 442\n",
      "0.614035087719\n",
      "Accuracy of k = 443\n",
      "0.614035087719\n",
      "Accuracy of k = 444\n",
      "0.614035087719\n",
      "Accuracy of k = 445\n",
      "0.614035087719\n",
      "Accuracy of k = 446\n",
      "0.614035087719\n",
      "Accuracy of k = 447\n",
      "0.614035087719\n",
      "Accuracy of k = 448\n",
      "0.614035087719\n",
      "Accuracy of k = 449\n",
      "0.614035087719\n",
      "Accuracy of k = 450\n",
      "0.614035087719\n",
      "Accuracy of k = 451\n",
      "0.614035087719\n",
      "Accuracy of k = 452\n",
      "0.614035087719\n",
      "Accuracy of k = 453\n",
      "0.614035087719\n",
      "Accuracy of k = 454\n",
      "0.614035087719\n"
     ]
    }
   ],
   "source": [
    "knn_class = []\n",
    "for i in range(1, 455):\n",
    "    knn_class = knn(n_neighbors = i)\n",
    "    knn_class.fit(train_x, train_y)\n",
    "    y_pred = knn_class.predict(test_x)\n",
    "    print(\"Accuracy of k =\" , i)\n",
    "    print(metrics.accuracy_score(y_pred, test_y))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "z_score = preprocessing.StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_scaled1 = z_score.fit_transform(data1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data3 = pd.DataFrame(data_scaled1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "         7         8         9     ...           20        21        22  \\\n",
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       "\n",
       "         23        24        25        26        27        28        29  \n",
       "0 -0.582718  0.268776 -0.812128 -0.709978 -0.315133 -0.119321 -0.899721  \n",
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       "2 -0.719308  0.198638 -0.674722 -0.793935 -0.613574  0.157320 -0.284606  \n",
       "3 -0.785054  0.189871 -0.458434 -0.889933 -0.433901 -1.292212 -0.892517  \n",
       "4 -0.108082 -0.866574 -0.512506 -0.652408 -0.499832 -0.669366 -0.902492  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data3[30] = data[\"diagnosis\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>...</td>\n",
       "      <td>0.124213</td>\n",
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       "      <td>-0.719308</td>\n",
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       "      <td>-0.674722</td>\n",
       "      <td>-0.793935</td>\n",
       "      <td>-0.613574</td>\n",
       "      <td>0.157320</td>\n",
       "      <td>-0.284606</td>\n",
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       "      <th>3</th>\n",
       "      <td>-0.808671</td>\n",
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       "      <td>-0.781338</td>\n",
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       "      <td>-0.889933</td>\n",
       "      <td>-0.433901</td>\n",
       "      <td>-1.292212</td>\n",
       "      <td>-0.892517</td>\n",
       "      <td>B</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.301824</td>\n",
       "      <td>-1.414775</td>\n",
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       "      <td>0.161860</td>\n",
       "      <td>-1.190618</td>\n",
       "      <td>-0.663320</td>\n",
       "      <td>-0.688883</td>\n",
       "      <td>-0.576473</td>\n",
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       "      <td>-1.043018</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.619844</td>\n",
       "      <td>-0.082245</td>\n",
       "      <td>-0.108082</td>\n",
       "      <td>-0.866574</td>\n",
       "      <td>-0.512506</td>\n",
       "      <td>-0.652408</td>\n",
       "      <td>-0.499832</td>\n",
       "      <td>-0.669366</td>\n",
       "      <td>-0.902492</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
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       "         0         1         2         3         4         5         6   \\\n",
       "0 -0.513297 -1.605595 -0.540376 -0.542624  0.458285 -0.654413 -0.614306   \n",
       "1 -1.001801 -0.079038 -0.934566 -0.877375  0.036986  0.196319 -0.312987   \n",
       "2 -0.876835 -0.572377 -0.867014 -0.801153  0.806996 -0.498443 -0.732448   \n",
       "3 -0.808671 -1.372888 -0.781338 -0.768161  1.426135  0.175472 -0.532950   \n",
       "4  0.301824 -1.414775  0.234000  0.161860 -1.190618 -0.663320 -0.688883   \n",
       "\n",
       "         7         8         9  ...        21        22        23        24  \\\n",
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       "2 -0.622129 -0.356400  0.085395 ...  0.124213 -0.814083 -0.719308  0.198638   \n",
       "3 -0.024740 -0.148296 -0.294523 ... -1.613330 -0.915355 -0.785054  0.189871   \n",
       "4 -0.576473 -0.330843 -1.043018 ... -1.619844 -0.082245 -0.108082 -0.866574   \n",
       "\n",
       "         25        26        27        28        29  30  \n",
       "0 -0.812128 -0.709978 -0.315133 -0.119321 -0.899721   B  \n",
       "1 -0.017590 -0.386625 -0.538203  0.063489 -0.447528   B  \n",
       "2 -0.674722 -0.793935 -0.613574  0.157320 -0.284606   B  \n",
       "3 -0.458434 -0.889933 -0.433901 -1.292212 -0.892517   B  \n",
       "4 -0.512506 -0.652408 -0.499832 -0.669366 -0.902492   B  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 307,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "label_encoder = preprocessing.LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "label1 = label_encoder.fit_transform(data3[30])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "       1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1], dtype=int64)"
      ]
     },
     "execution_count": 310,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data3[30] = label1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [
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     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "data3.head()"
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  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_x1, test_x1, train_y1, test_y1 = train_test_split(data3.iloc[:, :-1],data3[30], test_size = 0.2)"
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  {
   "cell_type": "code",
   "execution_count": 314,
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       "\n",
       "[5 rows x 30 columns]"
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     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
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  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68     0\n",
       "6      0\n",
       "175    0\n",
       "7      1\n",
       "208    0\n",
       "Name: 30, dtype: int64"
      ]
     },
     "execution_count": 315,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_y1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "knn3 = knn(n_neighbors=21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=1, n_neighbors=21, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 317,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn3.fit(train_x1, train_y1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred1 = knn3.predict(test_x1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[74,  1],\n",
       "       [ 0, 39]], dtype=int64)"
      ]
     },
     "execution_count": 319,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.confusion_matrix(y_pred1, test_y1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.99122807017543857"
      ]
     },
     "execution_count": 320,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.accuracy_score(y_pred1,test_y1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(455, 30)"
      ]
     },
     "execution_count": 321,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_x1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of k = 1\n",
      "0.982456140351\n",
      "Accuracy of k = 2\n",
      "0.973684210526\n",
      "Accuracy of k = 3\n",
      "0.991228070175\n",
      "Accuracy of k = 4\n",
      "0.991228070175\n",
      "Accuracy of k = 5\n",
      "1.0\n",
      "Accuracy of k = 6\n",
      "0.991228070175\n",
      "Accuracy of k = 7\n",
      "1.0\n",
      "Accuracy of k = 8\n",
      "0.991228070175\n",
      "Accuracy of k = 9\n",
      "0.991228070175\n",
      "Accuracy of k = 10\n",
      "0.991228070175\n",
      "Accuracy of k = 11\n",
      "0.991228070175\n",
      "Accuracy of k = 12\n",
      "0.991228070175\n",
      "Accuracy of k = 13\n",
      "0.991228070175\n",
      "Accuracy of k = 14\n",
      "0.991228070175\n",
      "Accuracy of k = 15\n",
      "0.991228070175\n",
      "Accuracy of k = 16\n",
      "0.991228070175\n",
      "Accuracy of k = 17\n",
      "0.991228070175\n",
      "Accuracy of k = 18\n",
      "0.991228070175\n",
      "Accuracy of k = 19\n",
      "0.991228070175\n",
      "Accuracy of k = 20\n",
      "0.991228070175\n",
      "Accuracy of k = 21\n",
      "0.991228070175\n",
      "Accuracy of k = 22\n",
      "0.991228070175\n",
      "Accuracy of k = 23\n",
      "0.991228070175\n",
      "Accuracy of k = 24\n",
      "0.982456140351\n",
      "Accuracy of k = 25\n",
      "0.982456140351\n",
      "Accuracy of k = 26\n",
      "0.982456140351\n",
      "Accuracy of k = 27\n",
      "0.982456140351\n",
      "Accuracy of k = 28\n",
      "0.982456140351\n",
      "Accuracy of k = 29\n",
      "0.982456140351\n",
      "Accuracy of k = 30\n",
      "0.982456140351\n",
      "Accuracy of k = 31\n",
      "0.982456140351\n",
      "Accuracy of k = 32\n",
      "0.982456140351\n",
      "Accuracy of k = 33\n",
      "0.982456140351\n",
      "Accuracy of k = 34\n",
      "0.982456140351\n",
      "Accuracy of k = 35\n",
      "0.982456140351\n",
      "Accuracy of k = 36\n",
      "0.982456140351\n",
      "Accuracy of k = 37\n",
      "0.982456140351\n",
      "Accuracy of k = 38\n",
      "0.982456140351\n",
      "Accuracy of k = 39\n",
      "0.982456140351\n",
      "Accuracy of k = 40\n",
      "0.982456140351\n",
      "Accuracy of k = 41\n",
      "0.982456140351\n",
      "Accuracy of k = 42\n",
      "0.982456140351\n",
      "Accuracy of k = 43\n",
      "0.982456140351\n",
      "Accuracy of k = 44\n",
      "0.982456140351\n",
      "Accuracy of k = 45\n",
      "0.982456140351\n",
      "Accuracy of k = 46\n",
      "0.982456140351\n",
      "Accuracy of k = 47\n",
      "0.982456140351\n",
      "Accuracy of k = 48\n",
      "0.982456140351\n",
      "Accuracy of k = 49\n",
      "0.982456140351\n",
      "Accuracy of k = 50\n",
      "0.982456140351\n",
      "Accuracy of k = 51\n",
      "0.982456140351\n",
      "Accuracy of k = 52\n",
      "0.982456140351\n",
      "Accuracy of k = 53\n",
      "0.982456140351\n",
      "Accuracy of k = 54\n",
      "0.982456140351\n",
      "Accuracy of k = 55\n",
      "0.982456140351\n",
      "Accuracy of k = 56\n",
      "0.982456140351\n",
      "Accuracy of k = 57\n",
      "0.982456140351\n",
      "Accuracy of k = 58\n",
      "0.982456140351\n",
      "Accuracy of k = 59\n",
      "0.982456140351\n",
      "Accuracy of k = 60\n",
      "0.973684210526\n",
      "Accuracy of k = 61\n",
      "0.973684210526\n",
      "Accuracy of k = 62\n",
      "0.973684210526\n",
      "Accuracy of k = 63\n",
      "0.982456140351\n",
      "Accuracy of k = 64\n",
      "0.982456140351\n",
      "Accuracy of k = 65\n",
      "0.982456140351\n",
      "Accuracy of k = 66\n",
      "0.973684210526\n",
      "Accuracy of k = 67\n",
      "0.973684210526\n",
      "Accuracy of k = 68\n",
      "0.973684210526\n",
      "Accuracy of k = 69\n",
      "0.973684210526\n",
      "Accuracy of k = 70\n",
      "0.973684210526\n",
      "Accuracy of k = 71\n",
      "0.973684210526\n",
      "Accuracy of k = 72\n",
      "0.973684210526\n",
      "Accuracy of k = 73\n",
      "0.973684210526\n",
      "Accuracy of k = 74\n",
      "0.973684210526\n",
      "Accuracy of k = 75\n",
      "0.973684210526\n",
      "Accuracy of k = 76\n",
      "0.973684210526\n",
      "Accuracy of k = 77\n",
      "0.973684210526\n",
      "Accuracy of k = 78\n",
      "0.973684210526\n",
      "Accuracy of k = 79\n",
      "0.973684210526\n",
      "Accuracy of k = 80\n",
      "0.973684210526\n",
      "Accuracy of k = 81\n",
      "0.973684210526\n",
      "Accuracy of k = 82\n",
      "0.973684210526\n",
      "Accuracy of k = 83\n",
      "0.973684210526\n",
      "Accuracy of k = 84\n",
      "0.973684210526\n",
      "Accuracy of k = 85\n",
      "0.973684210526\n",
      "Accuracy of k = 86\n",
      "0.973684210526\n",
      "Accuracy of k = 87\n",
      "0.973684210526\n",
      "Accuracy of k = 88\n",
      "0.973684210526\n",
      "Accuracy of k = 89\n",
      "0.973684210526\n",
      "Accuracy of k = 90\n",
      "0.973684210526\n",
      "Accuracy of k = 91\n",
      "0.973684210526\n",
      "Accuracy of k = 92\n",
      "0.973684210526\n",
      "Accuracy of k = 93\n",
      "0.973684210526\n",
      "Accuracy of k = 94\n",
      "0.973684210526\n",
      "Accuracy of k = 95\n",
      "0.973684210526\n",
      "Accuracy of k = 96\n",
      "0.973684210526\n",
      "Accuracy of k = 97\n",
      "0.973684210526\n",
      "Accuracy of k = 98\n",
      "0.973684210526\n",
      "Accuracy of k = 99\n",
      "0.973684210526\n",
      "Accuracy of k = 100\n",
      "0.973684210526\n",
      "Accuracy of k = 101\n",
      "0.973684210526\n",
      "Accuracy of k = 102\n",
      "0.973684210526\n",
      "Accuracy of k = 103\n",
      "0.973684210526\n",
      "Accuracy of k = 104\n",
      "0.973684210526\n",
      "Accuracy of k = 105\n",
      "0.964912280702\n",
      "Accuracy of k = 106\n",
      "0.973684210526\n",
      "Accuracy of k = 107\n",
      "0.973684210526\n",
      "Accuracy of k = 108\n",
      "0.973684210526\n",
      "Accuracy of k = 109\n",
      "0.964912280702\n",
      "Accuracy of k = 110\n",
      "0.947368421053\n",
      "Accuracy of k = 111\n",
      "0.947368421053\n",
      "Accuracy of k = 112\n",
      "0.956140350877\n",
      "Accuracy of k = 113\n",
      "0.964912280702\n",
      "Accuracy of k = 114\n",
      "0.973684210526\n",
      "Accuracy of k = 115\n",
      "0.964912280702\n",
      "Accuracy of k = 116\n",
      "0.964912280702\n",
      "Accuracy of k = 117\n",
      "0.964912280702\n",
      "Accuracy of k = 118\n",
      "0.964912280702\n",
      "Accuracy of k = 119\n",
      "0.964912280702\n",
      "Accuracy of k = 120\n",
      "0.956140350877\n",
      "Accuracy of k = 121\n",
      "0.956140350877\n",
      "Accuracy of k = 122\n",
      "0.956140350877\n",
      "Accuracy of k = 123\n",
      "0.964912280702\n",
      "Accuracy of k = 124\n",
      "0.964912280702\n",
      "Accuracy of k = 125\n",
      "0.964912280702\n",
      "Accuracy of k = 126\n",
      "0.947368421053\n",
      "Accuracy of k = 127\n",
      "0.956140350877\n",
      "Accuracy of k = 128\n",
      "0.947368421053\n",
      "Accuracy of k = 129\n",
      "0.964912280702\n",
      "Accuracy of k = 130\n",
      "0.956140350877\n",
      "Accuracy of k = 131\n",
      "0.964912280702\n",
      "Accuracy of k = 132\n",
      "0.964912280702\n",
      "Accuracy of k = 133\n",
      "0.964912280702\n",
      "Accuracy of k = 134\n",
      "0.947368421053\n",
      "Accuracy of k = 135\n",
      "0.947368421053\n",
      "Accuracy of k = 136\n",
      "0.947368421053\n",
      "Accuracy of k = 137\n",
      "0.947368421053\n",
      "Accuracy of k = 138\n",
      "0.947368421053\n",
      "Accuracy of k = 139\n",
      "0.947368421053\n",
      "Accuracy of k = 140\n",
      "0.947368421053\n",
      "Accuracy of k = 141\n",
      "0.947368421053\n",
      "Accuracy of k = 142\n",
      "0.947368421053\n",
      "Accuracy of k = 143\n",
      "0.947368421053\n",
      "Accuracy of k = 144\n",
      "0.947368421053\n",
      "Accuracy of k = 145\n",
      "0.947368421053\n",
      "Accuracy of k = 146\n",
      "0.947368421053\n",
      "Accuracy of k = 147\n",
      "0.947368421053\n",
      "Accuracy of k = 148\n",
      "0.947368421053\n",
      "Accuracy of k = 149\n",
      "0.947368421053\n",
      "Accuracy of k = 150\n",
      "0.938596491228\n",
      "Accuracy of k = 151\n",
      "0.938596491228\n",
      "Accuracy of k = 152\n",
      "0.938596491228\n",
      "Accuracy of k = 153\n",
      "0.938596491228\n",
      "Accuracy of k = 154\n",
      "0.938596491228\n",
      "Accuracy of k = 155\n",
      "0.938596491228\n",
      "Accuracy of k = 156\n",
      "0.938596491228\n",
      "Accuracy of k = 157\n",
      "0.938596491228\n",
      "Accuracy of k = 158\n",
      "0.938596491228\n",
      "Accuracy of k = 159\n",
      "0.938596491228\n",
      "Accuracy of k = 160\n",
      "0.938596491228\n",
      "Accuracy of k = 161\n",
      "0.938596491228\n",
      "Accuracy of k = 162\n",
      "0.938596491228\n",
      "Accuracy of k = 163\n",
      "0.938596491228\n",
      "Accuracy of k = 164\n",
      "0.938596491228\n",
      "Accuracy of k = 165\n",
      "0.938596491228\n",
      "Accuracy of k = 166\n",
      "0.938596491228\n",
      "Accuracy of k = 167\n",
      "0.938596491228\n",
      "Accuracy of k = 168\n",
      "0.938596491228\n",
      "Accuracy of k = 169\n",
      "0.938596491228\n",
      "Accuracy of k = 170\n",
      "0.938596491228\n",
      "Accuracy of k = 171\n",
      "0.938596491228\n",
      "Accuracy of k = 172\n",
      "0.929824561404\n",
      "Accuracy of k = 173\n",
      "0.929824561404\n",
      "Accuracy of k = 174\n",
      "0.929824561404\n",
      "Accuracy of k = 175\n",
      "0.929824561404\n",
      "Accuracy of k = 176\n",
      "0.929824561404\n",
      "Accuracy of k = 177\n",
      "0.929824561404\n",
      "Accuracy of k = 178\n",
      "0.929824561404\n",
      "Accuracy of k = 179\n",
      "0.929824561404\n",
      "Accuracy of k = 180\n",
      "0.929824561404\n",
      "Accuracy of k = 181\n",
      "0.929824561404\n",
      "Accuracy of k = 182\n",
      "0.921052631579\n",
      "Accuracy of k = 183\n",
      "0.921052631579\n",
      "Accuracy of k = 184\n",
      "0.921052631579\n",
      "Accuracy of k = 185\n",
      "0.921052631579\n",
      "Accuracy of k = 186\n",
      "0.921052631579\n",
      "Accuracy of k = 187\n",
      "0.921052631579\n",
      "Accuracy of k = 188\n",
      "0.921052631579\n",
      "Accuracy of k = 189\n",
      "0.921052631579\n",
      "Accuracy of k = 190\n",
      "0.912280701754\n",
      "Accuracy of k = 191\n",
      "0.912280701754\n",
      "Accuracy of k = 192\n",
      "0.912280701754\n",
      "Accuracy of k = 193\n",
      "0.912280701754\n",
      "Accuracy of k = 194\n",
      "0.912280701754\n",
      "Accuracy of k = 195\n",
      "0.912280701754\n",
      "Accuracy of k = 196\n",
      "0.912280701754\n",
      "Accuracy of k = 197\n",
      "0.912280701754\n",
      "Accuracy of k = 198\n",
      "0.912280701754\n",
      "Accuracy of k = 199\n",
      "0.912280701754\n",
      "Accuracy of k = 200\n",
      "0.912280701754\n",
      "Accuracy of k = 201\n",
      "0.912280701754\n",
      "Accuracy of k = 202\n",
      "0.912280701754\n",
      "Accuracy of k = 203\n",
      "0.912280701754\n",
      "Accuracy of k = 204\n",
      "0.912280701754\n",
      "Accuracy of k = 205\n",
      "0.912280701754\n",
      "Accuracy of k = 206\n",
      "0.912280701754\n",
      "Accuracy of k = 207\n",
      "0.912280701754\n",
      "Accuracy of k = 208\n",
      "0.912280701754\n",
      "Accuracy of k = 209\n",
      "0.912280701754\n",
      "Accuracy of k = 210\n",
      "0.912280701754\n",
      "Accuracy of k = 211\n",
      "0.912280701754\n",
      "Accuracy of k = 212\n",
      "0.912280701754\n",
      "Accuracy of k = 213\n",
      "0.912280701754\n",
      "Accuracy of k = 214\n",
      "0.912280701754\n",
      "Accuracy of k = 215\n",
      "0.912280701754\n",
      "Accuracy of k = 216\n",
      "0.912280701754\n",
      "Accuracy of k = 217\n",
      "0.912280701754\n",
      "Accuracy of k = 218\n",
      "0.912280701754\n",
      "Accuracy of k = 219\n",
      "0.912280701754\n",
      "Accuracy of k = 220\n",
      "0.90350877193\n",
      "Accuracy of k = 221\n",
      "0.90350877193\n",
      "Accuracy of k = 222\n",
      "0.90350877193\n",
      "Accuracy of k = 223\n",
      "0.90350877193\n",
      "Accuracy of k = 224\n",
      "0.90350877193\n",
      "Accuracy of k = 225\n",
      "0.90350877193\n",
      "Accuracy of k = 226\n",
      "0.90350877193\n",
      "Accuracy of k = 227\n",
      "0.90350877193\n",
      "Accuracy of k = 228\n",
      "0.894736842105\n",
      "Accuracy of k = 229\n",
      "0.90350877193\n",
      "Accuracy of k = 230\n",
      "0.90350877193\n",
      "Accuracy of k = 231\n",
      "0.90350877193\n",
      "Accuracy of k = 232\n",
      "0.90350877193\n",
      "Accuracy of k = 233\n",
      "0.90350877193\n",
      "Accuracy of k = 234\n",
      "0.912280701754\n",
      "Accuracy of k = 235\n",
      "0.912280701754\n",
      "Accuracy of k = 236\n",
      "0.912280701754\n",
      "Accuracy of k = 237\n",
      "0.912280701754\n",
      "Accuracy of k = 238\n",
      "0.894736842105\n",
      "Accuracy of k = 239\n",
      "0.894736842105\n",
      "Accuracy of k = 240\n",
      "0.894736842105\n",
      "Accuracy of k = 241\n",
      "0.90350877193\n",
      "Accuracy of k = 242\n",
      "0.894736842105\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of k = 243\n",
      "0.894736842105\n",
      "Accuracy of k = 244\n",
      "0.894736842105\n",
      "Accuracy of k = 245\n",
      "0.90350877193\n",
      "Accuracy of k = 246\n",
      "0.894736842105\n",
      "Accuracy of k = 247\n",
      "0.894736842105\n",
      "Accuracy of k = 248\n",
      "0.894736842105\n",
      "Accuracy of k = 249\n",
      "0.90350877193\n",
      "Accuracy of k = 250\n",
      "0.894736842105\n",
      "Accuracy of k = 251\n",
      "0.90350877193\n",
      "Accuracy of k = 252\n",
      "0.894736842105\n",
      "Accuracy of k = 253\n",
      "0.90350877193\n",
      "Accuracy of k = 254\n",
      "0.90350877193\n",
      "Accuracy of k = 255\n",
      "0.90350877193\n",
      "Accuracy of k = 256\n",
      "0.885964912281\n",
      "Accuracy of k = 257\n",
      "0.894736842105\n",
      "Accuracy of k = 258\n",
      "0.877192982456\n",
      "Accuracy of k = 259\n",
      "0.885964912281\n",
      "Accuracy of k = 260\n",
      "0.885964912281\n",
      "Accuracy of k = 261\n",
      "0.885964912281\n",
      "Accuracy of k = 262\n",
      "0.877192982456\n",
      "Accuracy of k = 263\n",
      "0.877192982456\n",
      "Accuracy of k = 264\n",
      "0.877192982456\n",
      "Accuracy of k = 265\n",
      "0.877192982456\n",
      "Accuracy of k = 266\n",
      "0.868421052632\n",
      "Accuracy of k = 267\n",
      "0.868421052632\n",
      "Accuracy of k = 268\n",
      "0.868421052632\n",
      "Accuracy of k = 269\n",
      "0.868421052632\n",
      "Accuracy of k = 270\n",
      "0.850877192982\n",
      "Accuracy of k = 271\n",
      "0.850877192982\n",
      "Accuracy of k = 272\n",
      "0.850877192982\n",
      "Accuracy of k = 273\n",
      "0.850877192982\n",
      "Accuracy of k = 274\n",
      "0.850877192982\n",
      "Accuracy of k = 275\n",
      "0.850877192982\n",
      "Accuracy of k = 276\n",
      "0.850877192982\n",
      "Accuracy of k = 277\n",
      "0.850877192982\n",
      "Accuracy of k = 278\n",
      "0.850877192982\n",
      "Accuracy of k = 279\n",
      "0.850877192982\n",
      "Accuracy of k = 280\n",
      "0.850877192982\n",
      "Accuracy of k = 281\n",
      "0.850877192982\n",
      "Accuracy of k = 282\n",
      "0.842105263158\n",
      "Accuracy of k = 283\n",
      "0.842105263158\n",
      "Accuracy of k = 284\n",
      "0.842105263158\n",
      "Accuracy of k = 285\n",
      "0.842105263158\n",
      "Accuracy of k = 286\n",
      "0.842105263158\n",
      "Accuracy of k = 287\n",
      "0.842105263158\n",
      "Accuracy of k = 288\n",
      "0.842105263158\n",
      "Accuracy of k = 289\n",
      "0.842105263158\n",
      "Accuracy of k = 290\n",
      "0.833333333333\n",
      "Accuracy of k = 291\n",
      "0.833333333333\n",
      "Accuracy of k = 292\n",
      "0.824561403509\n",
      "Accuracy of k = 293\n",
      "0.833333333333\n",
      "Accuracy of k = 294\n",
      "0.824561403509\n",
      "Accuracy of k = 295\n",
      "0.824561403509\n",
      "Accuracy of k = 296\n",
      "0.824561403509\n",
      "Accuracy of k = 297\n",
      "0.824561403509\n",
      "Accuracy of k = 298\n",
      "0.824561403509\n",
      "Accuracy of k = 299\n",
      "0.824561403509\n",
      "Accuracy of k = 300\n",
      "0.824561403509\n",
      "Accuracy of k = 301\n",
      "0.824561403509\n",
      "Accuracy of k = 302\n",
      "0.824561403509\n",
      "Accuracy of k = 303\n",
      "0.824561403509\n",
      "Accuracy of k = 304\n",
      "0.815789473684\n",
      "Accuracy of k = 305\n",
      "0.815789473684\n",
      "Accuracy of k = 306\n",
      "0.798245614035\n",
      "Accuracy of k = 307\n",
      "0.798245614035\n",
      "Accuracy of k = 308\n",
      "0.798245614035\n",
      "Accuracy of k = 309\n",
      "0.798245614035\n",
      "Accuracy of k = 310\n",
      "0.798245614035\n",
      "Accuracy of k = 311\n",
      "0.798245614035\n",
      "Accuracy of k = 312\n",
      "0.798245614035\n",
      "Accuracy of k = 313\n",
      "0.798245614035\n",
      "Accuracy of k = 314\n",
      "0.780701754386\n",
      "Accuracy of k = 315\n",
      "0.780701754386\n",
      "Accuracy of k = 316\n",
      "0.780701754386\n",
      "Accuracy of k = 317\n",
      "0.780701754386\n",
      "Accuracy of k = 318\n",
      "0.771929824561\n",
      "Accuracy of k = 319\n",
      "0.771929824561\n",
      "Accuracy of k = 320\n",
      "0.771929824561\n",
      "Accuracy of k = 321\n",
      "0.771929824561\n",
      "Accuracy of k = 322\n",
      "0.771929824561\n",
      "Accuracy of k = 323\n",
      "0.771929824561\n",
      "Accuracy of k = 324\n",
      "0.754385964912\n",
      "Accuracy of k = 325\n",
      "0.754385964912\n",
      "Accuracy of k = 326\n",
      "0.754385964912\n",
      "Accuracy of k = 327\n",
      "0.754385964912\n",
      "Accuracy of k = 328\n",
      "0.736842105263\n",
      "Accuracy of k = 329\n",
      "0.736842105263\n",
      "Accuracy of k = 330\n",
      "0.728070175439\n",
      "Accuracy of k = 331\n",
      "0.728070175439\n",
      "Accuracy of k = 332\n",
      "0.69298245614\n",
      "Accuracy of k = 333\n",
      "0.69298245614\n",
      "Accuracy of k = 334\n",
      "0.675438596491\n",
      "Accuracy of k = 335\n",
      "0.675438596491\n",
      "Accuracy of k = 336\n",
      "0.675438596491\n",
      "Accuracy of k = 337\n",
      "0.675438596491\n",
      "Accuracy of k = 338\n",
      "0.657894736842\n",
      "Accuracy of k = 339\n",
      "0.657894736842\n",
      "Accuracy of k = 340\n",
      "0.649122807018\n",
      "Accuracy of k = 341\n",
      "0.649122807018\n",
      "Accuracy of k = 342\n",
      "0.649122807018\n",
      "Accuracy of k = 343\n",
      "0.649122807018\n",
      "Accuracy of k = 344\n",
      "0.649122807018\n",
      "Accuracy of k = 345\n",
      "0.649122807018\n",
      "Accuracy of k = 346\n",
      "0.649122807018\n",
      "Accuracy of k = 347\n",
      "0.649122807018\n",
      "Accuracy of k = 348\n",
      "0.649122807018\n",
      "Accuracy of k = 349\n",
      "0.649122807018\n",
      "Accuracy of k = 350\n",
      "0.649122807018\n",
      "Accuracy of k = 351\n",
      "0.649122807018\n",
      "Accuracy of k = 352\n",
      "0.649122807018\n",
      "Accuracy of k = 353\n",
      "0.649122807018\n",
      "Accuracy of k = 354\n",
      "0.649122807018\n",
      "Accuracy of k = 355\n",
      "0.649122807018\n",
      "Accuracy of k = 356\n",
      "0.649122807018\n",
      "Accuracy of k = 357\n",
      "0.649122807018\n",
      "Accuracy of k = 358\n",
      "0.649122807018\n",
      "Accuracy of k = 359\n",
      "0.649122807018\n",
      "Accuracy of k = 360\n",
      "0.649122807018\n",
      "Accuracy of k = 361\n",
      "0.649122807018\n",
      "Accuracy of k = 362\n",
      "0.649122807018\n",
      "Accuracy of k = 363\n",
      "0.649122807018\n",
      "Accuracy of k = 364\n",
      "0.649122807018\n",
      "Accuracy of k = 365\n",
      "0.649122807018\n",
      "Accuracy of k = 366\n",
      "0.649122807018\n",
      "Accuracy of k = 367\n",
      "0.649122807018\n",
      "Accuracy of k = 368\n",
      "0.649122807018\n",
      "Accuracy of k = 369\n",
      "0.649122807018\n",
      "Accuracy of k = 370\n",
      "0.649122807018\n",
      "Accuracy of k = 371\n",
      "0.649122807018\n",
      "Accuracy of k = 372\n",
      "0.649122807018\n",
      "Accuracy of k = 373\n",
      "0.649122807018\n",
      "Accuracy of k = 374\n",
      "0.649122807018\n",
      "Accuracy of k = 375\n",
      "0.649122807018\n",
      "Accuracy of k = 376\n",
      "0.649122807018\n",
      "Accuracy of k = 377\n",
      "0.649122807018\n",
      "Accuracy of k = 378\n",
      "0.649122807018\n",
      "Accuracy of k = 379\n",
      "0.649122807018\n",
      "Accuracy of k = 380\n",
      "0.649122807018\n",
      "Accuracy of k = 381\n",
      "0.649122807018\n",
      "Accuracy of k = 382\n",
      "0.649122807018\n",
      "Accuracy of k = 383\n",
      "0.649122807018\n",
      "Accuracy of k = 384\n",
      "0.649122807018\n",
      "Accuracy of k = 385\n",
      "0.649122807018\n",
      "Accuracy of k = 386\n",
      "0.649122807018\n",
      "Accuracy of k = 387\n",
      "0.649122807018\n",
      "Accuracy of k = 388\n",
      "0.649122807018\n",
      "Accuracy of k = 389\n",
      "0.649122807018\n",
      "Accuracy of k = 390\n",
      "0.649122807018\n",
      "Accuracy of k = 391\n",
      "0.649122807018\n",
      "Accuracy of k = 392\n",
      "0.649122807018\n",
      "Accuracy of k = 393\n",
      "0.649122807018\n",
      "Accuracy of k = 394\n",
      "0.649122807018\n",
      "Accuracy of k = 395\n",
      "0.649122807018\n",
      "Accuracy of k = 396\n",
      "0.649122807018\n",
      "Accuracy of k = 397\n",
      "0.649122807018\n",
      "Accuracy of k = 398\n",
      "0.649122807018\n",
      "Accuracy of k = 399\n",
      "0.649122807018\n",
      "Accuracy of k = 400\n",
      "0.649122807018\n",
      "Accuracy of k = 401\n",
      "0.649122807018\n",
      "Accuracy of k = 402\n",
      "0.649122807018\n",
      "Accuracy of k = 403\n",
      "0.649122807018\n",
      "Accuracy of k = 404\n",
      "0.649122807018\n",
      "Accuracy of k = 405\n",
      "0.649122807018\n",
      "Accuracy of k = 406\n",
      "0.649122807018\n",
      "Accuracy of k = 407\n",
      "0.649122807018\n",
      "Accuracy of k = 408\n",
      "0.649122807018\n",
      "Accuracy of k = 409\n",
      "0.649122807018\n",
      "Accuracy of k = 410\n",
      "0.649122807018\n",
      "Accuracy of k = 411\n",
      "0.649122807018\n",
      "Accuracy of k = 412\n",
      "0.649122807018\n",
      "Accuracy of k = 413\n",
      "0.649122807018\n",
      "Accuracy of k = 414\n",
      "0.649122807018\n",
      "Accuracy of k = 415\n",
      "0.649122807018\n",
      "Accuracy of k = 416\n",
      "0.649122807018\n",
      "Accuracy of k = 417\n",
      "0.649122807018\n",
      "Accuracy of k = 418\n",
      "0.649122807018\n",
      "Accuracy of k = 419\n",
      "0.649122807018\n",
      "Accuracy of k = 420\n",
      "0.649122807018\n",
      "Accuracy of k = 421\n",
      "0.649122807018\n",
      "Accuracy of k = 422\n",
      "0.649122807018\n",
      "Accuracy of k = 423\n",
      "0.649122807018\n",
      "Accuracy of k = 424\n",
      "0.649122807018\n",
      "Accuracy of k = 425\n",
      "0.649122807018\n",
      "Accuracy of k = 426\n",
      "0.649122807018\n",
      "Accuracy of k = 427\n",
      "0.649122807018\n",
      "Accuracy of k = 428\n",
      "0.649122807018\n",
      "Accuracy of k = 429\n",
      "0.649122807018\n",
      "Accuracy of k = 430\n",
      "0.649122807018\n",
      "Accuracy of k = 431\n",
      "0.649122807018\n",
      "Accuracy of k = 432\n",
      "0.649122807018\n",
      "Accuracy of k = 433\n",
      "0.649122807018\n",
      "Accuracy of k = 434\n",
      "0.649122807018\n",
      "Accuracy of k = 435\n",
      "0.649122807018\n",
      "Accuracy of k = 436\n",
      "0.649122807018\n",
      "Accuracy of k = 437\n",
      "0.649122807018\n",
      "Accuracy of k = 438\n",
      "0.649122807018\n",
      "Accuracy of k = 439\n",
      "0.649122807018\n",
      "Accuracy of k = 440\n",
      "0.649122807018\n",
      "Accuracy of k = 441\n",
      "0.649122807018\n",
      "Accuracy of k = 442\n",
      "0.649122807018\n",
      "Accuracy of k = 443\n",
      "0.649122807018\n",
      "Accuracy of k = 444\n",
      "0.649122807018\n",
      "Accuracy of k = 445\n",
      "0.649122807018\n",
      "Accuracy of k = 446\n",
      "0.649122807018\n",
      "Accuracy of k = 447\n",
      "0.649122807018\n",
      "Accuracy of k = 448\n",
      "0.649122807018\n",
      "Accuracy of k = 449\n",
      "0.649122807018\n",
      "Accuracy of k = 450\n",
      "0.649122807018\n",
      "Accuracy of k = 451\n",
      "0.649122807018\n",
      "Accuracy of k = 452\n",
      "0.649122807018\n",
      "Accuracy of k = 453\n",
      "0.649122807018\n",
      "Accuracy of k = 454\n",
      "0.649122807018\n"
     ]
    }
   ],
   "source": [
    "knn_class = []\n",
    "for i in range(1, 455):\n",
    "    knn_class = knn(n_neighbors = i)\n",
    "    knn_class.fit(train_x1, train_y1)\n",
    "    y_pred1 = knn_class.predict(test_x1)\n",
    "    print(\"Accuracy of k =\" , i)\n",
    "    print(metrics.accuracy_score(y_pred1, test_y1))\n",
    "    "
   ]
  }
 ],
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