#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()
When I call model.fit it reports the following error :
ValueError: Error when checking target: expected activation_5 to have shape (None, 2) but got array with shape (3869, 1)
I am using keras with TensorFlow backend. Please ask for any further clarification if needed.