hello scikit-learn devs,
After following the work on IsolationForest so far and testing on a
real-world problem here we've found this model to be very promising for
anomaly detection. However, at present, IsolationForest only fits data
in batch even while it may be well suited to incremental on-line
learning since one could subsample recent history and older estimators
can be dropped progressively.
I'd like to contribute this feature, but being new to ML and
scikit-learn I'm curious how I should start making a quick & dirty
version to see how this may work. Are there other good examples where
one could see the difference between .fit and .partial_fit in other
models?
thanks
isaak y.
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