使用KNN算法手写体识别
-
-
-
- import numpy as np
- import operator
- import matplotlib
- import matplotlib.pyplot as plt
- import os
-
- ''
-
-
-
-
-
-
-
-
- ''
-
-
-
-
-
- def classify0(inX , dataSet , labels , k):
- dataSetSize = dataSet.shape[0]
- diffMat = np.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)
- print sortedClassCount
- return sortedClassCount[0][0]
-
-
- ''
-
-
- def img2vector(filename):
- returnVect = np.zeros((1,1024))
- fr = open(filename)
- for i in range(32):
- line = fr.readline()
- for j in range(32):
- returnVect[0,i*32+j] = int(line[j] )
- return returnVect
-
- ''
-
-
- def handwritingClassTest(trainFilePath,testFilePath):
- hwLabels = []
- trainingFileList = os.listdir(trainFilePath)
- m=len(trainingFileList)
- trainSet = np.zeros((m,1024))
- for i in range(m):
- filename = trainingFileList[i]
- classNum = filename.split('.')[0]
- classNum = int(classNum.split('_')[0])
- hwLabels.append(classNum)
- trainSet[i] = img2vector( os.path.join(trainFilePath,filename) )
- testFileList = os.listdir(testFilePath)
- errorCount = 0
- mTest = len(testFileList)
- for i in range(mTest):
- filename = trainingFileList[i]
- classNum = filename.split('.')[0]
- classNum = int(classNum.split('_')[0])
- vectorUnderTest = img2vector(os.path.join(trainFilePath, filename))
- classifyNum = classify0(vectorUnderTest,trainSet,hwLabels,10)
- print "the classifier came back with : %d , the real answer is : %d"% (classifyNum , classNum)
- if(classifyNum != classNum) : errorCount+=1
- print ("
the total number of error is : %d"%errorCount)
- print ("
the error rate is : %f"%(float(errorCount)/mTest))
- handwritingClassTest()
原文地址:https://www.cnblogs.com/Lambda721/p/8397453.html