def get_bpnn_predict(X, y, param):
model = BPNN(learning_rate=0.05,
num_of_training=100,
input_size=X.shape[1],
hidden_n=2,
parameters=list(param))
model.fit(X, y)
predvalue = model.predict(X)
return np.array(predvalue)
