Do you need to store your old data to refit a model in sklearn?
In general, only the estimators implementing the partial_fit method are able to do this. Unfortunately, IsolationForest is not one of them.
I am trying to use sklearn to build an Isolation Forest machine learning program to go through a ton of data. I can only store the past 10 days of data, so I was wondering:
When I use the "fit" function on new data that comes in, does it refit the model considering the hyper-parameters from the old data without having had access to that old data anymore? Or is it completely recreating the model?