python 3.x - 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'     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()

when call model.fit it reports following error :

valueerror: error when checking target: expected activation_5 have shape (none, 2) got array shape (3869, 1)

i using keras tensorflow backend. please ask further clarification if needed.

the problem solved when used statement 

y = to_categorical(y[:])

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