Why am I getting "Supported target types are: ('binary', 'multiclass'). Got 'continuous' instead." error?

Question

I am writing this code and keep getting the Supported target types are: ('binary', 'multiclass'). Got 'continuous' instead. error no matter what I try. Do you see the problem within my code?

df = pd.read_csv('drain.csv')
values = df.values
seed = 7
numpy.random.seed(seed)
X = df.iloc[:,:2]
Y = df.iloc[:,2:]
def create_model():
# create model
    model = Sequential()
    model.add(Dense(12, input_dim=8, activation='relu'))
    model.add(Dense(8, activation='relu'))
    model.add(Dense(1, activation='sigmoid'))
    # Compile model
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model
model = KerasClassifier(build_fn=create_model, epochs=10, batch_size=10, verbose=0)
# evaluate using 10-fold cross validation
kfold = StratifiedKFold(n_splits=10, shuffle=True, random_state=seed)
results = cross_val_score(model, X, Y, cv=kfold)
print(results.mean())

Answer 1

You need to convert your Y variables to binary, as specified here : https://github.com/keras-team/keras/blob/master/examples/mnist_mlp.py

# convert class vectors to binary class matrices
y_train = keras.utils.to_categorical(y_train, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)

and then

history = model.fit(x_train, y_train,
                    batch_size=batch_size,
                    epochs=epochs,
                    verbose=1,
                    validation_data=(x_test, y_test))

Seems like you forgot the conversion to categorical step.