In my problem I have a longer period of historical data of a time series. I need to predict for some specific points in time in the future. For these points in time five previous values are also available.
So far my approach was to use a sliding window of size five, use lag features and apply machine learning methods.
However I have a feeling that when doing like this I am not exploiting the historical data to the full extent. (The methods see only one sliding window at a time.)
I am now looking for some method (or ideas to design my own) which takes as an input historical data and measurements just before the time point I need to predict for.