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更新2.KNN文件位置

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jiangzhonglian
2017-04-07 16:07:15 +08:00
parent 5857502a77
commit a1b25f1637
2882 changed files with 5 additions and 5 deletions
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10
src/python/02.kNN/kNN.py
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@@ -151,7 +151,7 @@ def datingClassTest():
# 设置测试数据的的一个比例（训练数据集比例=1-hoRatio）
hoRatio = 0.1 # 测试范围,一部分测试一部分作为样本
# 从文件中加载数据
datingDataMat, datingLabels = file2matrix('testData/datingTestSet2.txt') # load data setfrom file
datingDataMat, datingLabels = file2matrix('input/02.KNN/datingTestSet2.txt') # load data setfrom file
# 归一化数据
normMat, ranges, minVals = autoNorm(datingDataMat)
m = normMat.shape[0]
@@ -186,7 +186,7 @@ def img2vector(filename):
def handwritingClassTest():
# 1. 导入数据
hwLabels = []
trainingFileList = listdir('testData/trainingDigits') # load the training set
trainingFileList = listdir('input/02.KNN/trainingDigits') # load the training set
m = len(trainingFileList)
trainingMat = zeros((m, 1024))
# hwLabels存储0～9对应的index位置， trainingMat存放的每个位置对应的图片向量
@@ -195,17 +195,17 @@ def handwritingClassTest():
fileStr = fileNameStr.split('.')[0] # take off .txt
classNumStr = int(fileStr.split('_')[0])
hwLabels.append(classNumStr)
trainingMat[i, :] = img2vector('testData/trainingDigits/%s' % fileNameStr)
trainingMat[i, :] = img2vector('input/02.KNN/trainingDigits/%s' % fileNameStr)
# 2. 导入测试数据
testFileList = listdir('testData/testDigits') # iterate through the test set
testFileList = listdir('input/02.KNN/testDigits') # iterate through the test set
errorCount = 0.0
mTest = len(testFileList)
for i in range(mTest):
fileNameStr = testFileList[i]
fileStr = fileNameStr.split('.')[0] # take off .txt
classNumStr = int(fileStr.split('_')[0])
vectorUnderTest = img2vector('testData/testDigits/%s' % fileNameStr)
vectorUnderTest = img2vector('input/02.KNN/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 += 1.0