Hi @ptrblck,
I use minmax scaler from sklearn.
scaler = MinMaxScaler(feature_range=(-1,1))
scaler = scaler.fit(features_df)
dummy_data = scaler.data_max_ + 5, scaler.data_min_ - 5
scaler = scaler.fit(dummy_data)
scaler.transform(train_df)
After trained and test,
descaler =MinMaxScaler()
descaler.min_, descaler.scale_ = scaler.min_[2], scaler.scale_[2]
def descale(descaler, values):
values_2d = np.array(values)
return descaler.inverse_transform(values_2d)
predictions_descaled = descale(descaler, sq)
speed_labels_descaled = descale(descaler, speed_labels)
The high MSE loss happened after I use predictions_descaled and speed_labels_descaled
Thanks