[scikit-learn] partial_fit implementation for IsolationForest

[Arthur Mensch]

Hi Isaac,

You may have a look at MiniBatchKMeans and MiniBatchDictionaryLearning that
both proposes this API. At the moment, you should fit a single mini batch
to the estimator using partial_fit, and update the inner attributes
accordingly. During the first partial_fit, you should take care of various
memory allocation that are needed by the estimator.

Please fill free to create a pull request whenever you think your code is
ready for review.

Good luck!
Le 26 mai 2016 13:14, <donkey-hotei at cryptolab.net> a écrit :

> 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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