Finance, Python, Deep Learning, Analytics, Artificial Intelligence.
model_fit = model.fit(disp=0) # Make the prediction output = model_fit.forecast() yhat = output[0] return yhat # Split data into train and test sets X = dataset_ex_df.values size = int(len(X) * 0.8) train, test = X[0:size], X[size:len(X)] # Walk-forward validation history = [x for x in train]