training.py 文件源码

def trainLimitedSoftmax(self, featureFile, n_datapoints):
    (label_vector, input_vector) = self.__loadData__(featureFile)

    n_totalrows = int((len(label_vector)/n_datapoints))
    k=[]
    trainData, testData, trainLabels, testLabels = \
        cross_validation.train_test_split(input_vector, label_vector, test_size=(0.2))

    for n in range(0, n_totalrows):

      limited_label_vector = trainLabels[0: (n+1) * n_datapoints]
      limited_input_vector = trainData[0: (n+1) * n_datapoints]

      _, maxVal = self.trainSoftmaxWithData(limited_input_vector, limited_label_vector, 1000)

      print 'Total Average Value: %s \n\n' % (maxVal)
      k.append(maxVal)

    print('Limited Softmax training result ----------')
    for i in range (0,len(k)):
      print '%f on %d datapoints' % (k[i], (n_datapoints * (i+1)))
    print '------------------------------------------'