KMeanPackage.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%run KMeanModule.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data=pd.read_excel('K_means_data.xlsx')\n",
    "X=np.array(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "test=KMean(X,no_K=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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77Tlbq8Wp1/SuftKoMoCQCk6YM5zmk8fSaLVo1dxqUfW+4MRmqjsDCElDbT43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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x208e9260588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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BoKfUu1D2qol9PlC5YmW5K/ryif3R1AvxRoAA0DO4UNZ2/MAst9/TmXogWQgQAHoGF8ra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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x208e9767eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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gNAIEAAAIjQABAABCmxd1BQAA8TGxTzp2QFp0gbR4VdS1QZwRIAB0JS6U5bLHpOtfLx3Y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\ngAAAAKH9F+eHY52+ioFGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x208e95b1d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hmp1apJnJnqhCQ4xQAwE02YJkUufOmkXygFib37tKs1OLispmpxZpfu+qiCJC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x208e8149978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4A0GZyozr4ZFtOjq+/0Tb7K6lWtizXqlUV4KRIRT0QACNsH9/+eP79jUmDqBC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\nAAAQGwkEAACI7b8BTEz4ubWykw4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x208e931f780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AxMfwfmnkkDR3qdTZHXU0iDMSCAAtiRvlRKkRaftG6dCOM21L1kobBqXknOjiQnyRQABo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\nAACh/Q9bJ+v2ZTO2LwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x208e9393c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test.Run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no_K: 4\n",
      "iterations: 5\n",
      "plot: True\n"
     ]
    }
   ],
   "source": [
    "test.Get_Parameters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 5.38423044  5.17133492]\n",
      " [-5.72882791 -0.70942653]\n",
      " [ 3.33835619 -4.80522897]\n",
      " [-3.67964977  4.5454365 ]]\n"
     ]
    }
   ],
   "source": [
    "test.Get_Kmeans()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-4.68710272,  6.45669487,  3.        ],\n",
       "       [-8.12999156,  4.1410344 ,  1.        ],\n",
       "       [-5.43439621,  3.881037  ,  1.        ],\n",
       "       [-7.33296878,  6.95949262,  1.        ],\n",
       "       [-4.93458734,  7.22975143,  3.        ],\n",
       "       [-7.4896718 ,  3.02003088,  1.        ],\n",
       "       [-1.87484413,  5.51603382,  3.        ],\n",
       "       [-4.97059844,  3.05046378,  1.        ],\n",
       "       [-5.99853601,  5.75636707,  1.        ],\n",
       "       [-4.51182837,  5.73916542,  3.        ],\n",
       "       [-3.14754034, -3.68625131,  1.        ],\n",
       "       [-5.58857773, -4.8599815 ,  1.        ],\n",
       "       [-4.1796733 , -3.76076744,  1.        ],\n",
       "       [-2.83257838, -8.19647793,  2.        ],\n",
       "       [-5.45574962, -5.25754811,  1.        ],\n",
       "       [-7.33644027, -5.56701191,  1.        ],\n",
       "       [-4.91977669, -6.21665074,  1.        ],\n",
       "       [-6.70173405, -4.42660888,  1.        ],\n",
       "       [-2.38988628, -2.21446306,  3.        ],\n",
       "       [-3.51793591, -2.96557724,  1.        ],\n",
       "       [ 5.47383776, -8.41025058,  2.        ],\n",
       "       [ 1.92841215, -3.30186006,  2.        ],\n",
       "       [ 6.36940374, -3.89538595,  2.        ],\n",
       "       [ 4.88056732, -3.99483916,  2.        ],\n",
       "       [ 7.62379821, -6.34637945,  2.        ],\n",
       "       [ 1.72272452, -5.05212587,  2.        ],\n",
       "       [ 5.02563963, -2.3385923 ,  2.        ],\n",
       "       [ 1.34120124, -3.19901112,  2.        ],\n",
       "       [ 1.62195381, -4.59971961,  2.        ],\n",
       "       [ 3.56695806, -3.5228767 ,  2.        ],\n",
       "       [ 7.18431803,  2.95244027,  0.        ],\n",
       "       [ 4.53920772,  4.02586887,  0.        ],\n",
       "       [ 6.29101647,  4.51060155,  0.        ],\n",
       "       [ 3.98052773,  6.78598916,  0.        ],\n",
       "       [ 1.85125681,  8.03237048,  0.        ],\n",
       "       [ 4.82206677,  8.09637708,  0.        ],\n",
       "       [ 8.26052864,  3.09377197,  0.        ],\n",
       "       [ 4.40499971,  4.95032513,  0.        ],\n",
       "       [ 4.60913268,  6.29019916,  0.        ],\n",
       "       [ 7.89924988,  2.9754055 ,  0.        ]])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.Get_Output()"
   ]
  }
 ],
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