本文整理汇总了Python中classifier.Classifier.trainKNeighbors方法的典型用法代码示例。如果您正苦于以下问题：Python Classifier.trainKNeighbors方法的具体用法？Python Classifier.trainKNeighbors怎么用？Python Classifier.trainKNeighbors使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类classifier.Classifier的用法示例。
在下文中一共展示了Classifier.trainKNeighbors方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
# 需要导入模块: from classifier import Classifier [as 别名]
# 或者: from classifier.Classifier import trainKNeighbors [as 别名]
def main():
fileDir = 'trainingData.csv'
print("Parsing the training data from \'" + fileDir +"\'")
trainingSamples = parseFile(fileDir)
fileDir = 'Test01.csv'
print("Parsing the testing data from \'" + fileDir + "\'")
testingSamples = parseFile(fileDir)
c = Classifier()
print("Extracting features from the training samples")
c.extractTrainingFeatures(trainingSamples)
print("Extracting features from the testing samples")
c.extractTestingFeatures(testingSamples)
# testing number of samples correctly predicted
for i in range(1, 26) :
print("Training the model using a kNeighborsClassifier with k = " + str(i))
c.trainKNeighbors(i, 'distance')
out = c.testData()
percent = out[1] * 100
print("Accuracy: " + "{0:.2f}".format(percent) + "%\n")