K Nearest Neighbors (KNN) > Python Program

K Nearest Neighbors (KNN) > Python Program

Machine Learning

knn.py

from numpy import *

import operator

def createDataSet():

    group = array([[1.0,1.1],[1.0,1.0],[0,0],[0,0.1]])

    labels = ['A','A','B','B']

    return group, labels

def classify0(inX, dataSet, labels, k):

    dataSetSize = dataSet.shape[0]

    diffMat = tile(inX, (dataSetSize,1))-dataSet

    sqDiffMat = diffMat**2                           

    sqDistances = sqDiffMat.sum(axis=1)          

    distances = sqDistances**0.5                 

    sortedDistIndicies = distances.argsort()

    classCount={}

    for i in range(k):

        voteIlabel = labels[sortedDistIndicies[i]]  

        classCount[voteIlabel] = classCount.get(voteIlabel,0) + 1  

    sortedClassCount = sorted(classCount.items(),

    key=operator.itemgetter(1), reverse=True)       

    return sortedClassCount[0][0]

output:

================== RESTART: C:/Users/student/Desktop/knn.py ==================

>>> import knn

>>> group,labels = knn.createDataSet()

>>> group

array([[ 1. ,  1.1],

       [ 1. ,  1. ],

       [ 0. ,  0. ],

       [ 0. ,  0.1]])

>>> labels

['A', 'A', 'B', 'B']

>>> knn.classify0([0,0], group, labels, 3)

'B'

>>>