收到的标签值1超出有效范围[0，1)-Python，Keras

问题描述

我正在使用带有tensorflow背景的keras进行简单的cnn分类器工作.

I am working on a simple cnn classifier using keras with tensorflow background.

def cnnKeras(training_data, training_labels, test_data, test_labels, n_dim):
  print("Initiating CNN")
  seed = 8
  numpy.random.seed(seed)
  model = Sequential()
  model.add(Convolution2D(64, 1, 1, init='glorot_uniform',
   border_mode='valid',input_shape=(16, 1, 1), activation='relu'))
  model.add(MaxPooling2D(pool_size=(1, 1)))
  model.add(Convolution2D(32, 1, 1, init='glorot_uniform',
   activation='relu'))
  model.add(MaxPooling2D(pool_size=(1, 1)))
  model.add(Dropout(0.25))
  model.add(Flatten())
  model.add(Dense(128, activation='relu'))
  model.add(Dropout(0.5))
  model.add(Dense(64, activation='relu'))
  model.add(Dense(1, activation='softmax'))
  # Compile model
  model.compile(loss='sparse_categorical_crossentropy',
              optimizer='adam', metrics=['accuracy'])
  model.fit(training_data, training_labels, validation_data=(
    test_data, test_labels), nb_epoch=30, batch_size=8, verbose=2)

  scores = model.evaluate(test_data, test_labels, verbose=1)
  print("Baseline Error: %.2f%%" % (100 - scores[1] * 100))
  # model.save('trained_CNN.h5')
  return None

这是一个二进制分类问题，但我不断收到消息Received a label value of 1 which is outside the valid range of [0, 1)，这对我来说没有任何意义.有任何建议吗?

It is a binary classification problem, but I keep getting the message Received a label value of 1 which is outside the valid range of [0, 1) which does not make any sense to me. Any suggesstions?

推荐答案

Range [0, 1)表示0到1之间的每个数字，不包括1.因此1不在[0， 1).

Range [0, 1) means every number between 0 and 1, excluding 1. So 1 is not a value in the range [0, 1).

我不确定100％，但是问题可能是由于您选择了损失函数.对于二进制分类，binary_crossentropy应该是一个更好的选择.

I am not 100% sure, but the issue could be due to your choice of loss function. For a binary classification, binary_crossentropy should be a better choice.

这篇关于收到的标签值1超出有效范围[0，1)-Python，Keras的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！