KNN算法实现手写数字

from numpy import *

import operator

from os import listdir

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]

def img2Vector(filename):

    returnVect = zeros((1,1024))

    # print(returnVect)

    fr = open(filename)

    for i in range(32):

        lineStr = fr.readline()

        for j in range(32):

            returnVect[0,32*i+j] = int(lineStr[j])

    return returnVect

def handwritingClassTest():

    hwLabels = []

    trainingFileList = listdir('trainingDigits')

    m = len(trainingFileList)

    trainingMat = zeros((m,1024))

    for i in range(m):

        fileNameStr = trainingFileList[i]

        fileStr = fileNameStr.split('.')[0]

        classNumStr = int(fileStr.split('_')[0])

        hwLabels.append(classNumStr)

        trainingMat[i,:] = img2Vector('trainingDigits/%s'%fileNameStr)

    testFileList = listdir('testDigits')

    errorCount = 0.0

    mTest = len(testFileList)

    for i in range(mTest):

        fileNameStr = testFileList[i]

        fileStr = fileNameStr.split('.')[0]

        classNumStr = int(fileStr.split('_')[0])

        vectorUnderTest = img2Vector('testDigits/%s'%fileNameStr)

        classifierResult = classify0(vectorUnderTest,trainingMat,hwLabels,3)

        print("the classifier came back with:%d,the real answer is :%d"%(classifierResult,classNumStr))

        if (classifierResult != classNumStr):

            errorCount += 1

    print("the total number of errors is :%d"%errorCount)

    print("the total error rate is: %f"%(errorCount/float(mTest)))

handwritingClassTest()

测试集+训练集数据地址：https://i.cnblogs.com/Files.aspx

knn.rar