[python]k-近邻算法

2016-6-7 萧 写技术

书上把kNN抄了一遍，跑起来爽爽的： 

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.iteritems(),
	 key=operator.itemgetter(1),reverse = True)
	return sortedClassCount[0][0]

标签: python machine_learning

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