[英]Error in last layer of neural network
#10-Fold split
seed = 7
kfold = StratifiedKFold(n_splits=10, shuffle=True, random_state=seed)
np.random.seed(seed)
cvscores = []
act = 'relu'
for train, test in kfold.split(X, Y):
model = Sequential()
model.add(Dense(43, input_shape=(8,)))
model.add(Activation(act))
model.add(Dense(500))
model.add(Activation(act))
#model.add(Dropout(0.4))
model.add(Dense(1000))
model.add(Activation(act))
#model.add(Dropout(0.4))
model.add(Dense(1500))
model.add(Activation(act))
#model.add(Dropout(0.4))
model.add(Dense(2))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
hist = model.fit(X[train], Y[train],
epochs=500,
shuffle=True,
batch_size=100,
validation_data=(X[test], Y[test]), verbose=2)
#model.summary()
当我调用model.fit时,它报告以下错误:
ValueError:检查目标时出错:预期activation_5具有形状(无,2),但形状为数组(3869,1)
我在TensorFlow后端上使用keras 。 如果需要,请要求进一步的澄清。
尝试这个:
#10-Fold split
seed = 7
kfold = StratifiedKFold(n_splits=10, shuffle=True, random_state=seed)
np.random.seed(seed)
cvscores = []
act = 'relu'
for train, test in kfold.split(X, Y):
model = Sequential()
model.add(Dense(43, input_shape=(8,)))
model.add(Activation(act))
model.add(Dense(500))
model.add(Activation(act))
#model.add(Dropout(0.4))
model.add(Dense(1000))
model.add(Activation(act))
#model.add(Dropout(0.4))
model.add(Dense(1500))
model.add(Activation(act))
#model.add(Dropout(0.4))
model.add(Dense(1))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
hist = model.fit(X[train], Y[train],
epochs=500,
shuffle=True,
batch_size=100,
validation_data=(X[test], Y[test]), verbose=2)
#model.summary()
使用此语句时,问题已解决
y = to_categorical(Y[:])
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