mnist_train.csv下载_course

有mnist提供的手写数字训练集，每条数据的第一项是数字的正确结果，后784项是28*28手写图片的像素值，使用放在程序目录下 相关下载链接：//download.csdn.net/download/

kaggle fashion-mnist.csv python问题_course

>>> import csv >>> import KNN >>> from numpy import * >>> import operator >>> def toInt(array): arr

kaggle fashion-mnist.csv python的问题_course

本人python小白，在网上东拼西凑弄的代码 ``` >>> def toInt(array): array=mat(array) m,n=shape(array) newArray=zeros((m,n)) for i in range(m): for j in range(n): newArray[i,j]=int(array[i,j]) return newArray >>> def nomalizing(array): m,n=shape(array) for i in range(m): for j in range(n): if array[i,j]!=0: array[i,j]=1 return array >>> import csv >>> def loadTrainData(): l=[] with open('fashion-mnist_train.csv') as file: lines=csv.reader(file) for line in lines: l.append(line) l.remove(l[0]) l=array(l) label=l[:,0] data=l[:,1:] return nomalizing(toInt(data)),toInt(label) >>> def loadTestData(): l=[] with open('test_data.csv') as file: lines=csv.reader(file) for line in lines: l.append(line) l.remove(l[0]) l=array(l) data=l[:,1:] return nomalizing(toInt(data)) >>> def loadTestResult(): l=[] with open('sample_submission.csv') as file: lines=csv.reader(file) for line in lines: l.append(line) l.remove(l[0]) label=array(l) return toInt(label[:,1]) >>> def classify0(inX, dataSet, labels, k): inX=mat(inX) dataSet=mat(dataSet) labels=mat(labels) dataSetSize = dataSet.shape[0] diffMat = tile(inX, (dataSetSize,1)) - dataSet sqDiffMat = array(diffMat)**2 sqDistances = sqDiffMat.sum(axis=1) distances = sqDistances**0.5 sortedDistIndicies = distances.argsort() classCount={} for i in range(k): voteIlabel = labels[0,sortedDistIndicies[i]] classCount[voteIlabel] = classCount.get(voteIlabel,0) + 1 sortedClassCount = sorted(classCount.items(), key=operator.itemgetter(1), reverse=True) return sortedClassCount[0][0] >>> import KNN >>> from numpy import * >>> import operator >>> def handwritingClassTest(): trainData,trainLabel=loadTrainData() testData=loadTestData() testLabel=loadTestResult() m,n=shape(testData) errorCount=0 resultList=[] for i in range(m): classifierResult = classify0(testData[i], trainData, trainLabel, 5) resultList.append(classifierResult) print ("the classifier came back with: %d, the real answer is: %d") % (classifierResult, testLabel[0,i]) if (classifierResult != testLabel[0,i]): errorCount += 1.0 print ("\nthe total number of errors is: %d") % errorCount print ("\nthe total error rate is: %f") % (errorCount/float(m)) saveResult(resultList) >>> handwritingClassTest() ``` 运行了3个多小时，运行过程中的图片如下 结果如下  result.csv也在桌面上显示了，但是为0字节 求问各位大神，如何修改code呢？是不是再次运行还得3个小时呀、