To feed my generative neural net, I need to normalize some data between -1 and 1.
I do it with MinMaxScaler from Sklearn and it works great. Now, my generat
MinMaxScaler
def rev_min_max_func(scaled_val): max_val = max(df['target']) min_val = min(df['target']) og_val = (scaled_val*(max_val - min_val)) + min_val return og_val df['pred_target'] = scaled_labeled_df['pred_scaled_target'].apply(lambda x: rev_min_max_func(x))
Even this works for me!