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A python library for hierarchical classification compatible with scikit-learn

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Add probabilistic classification via calibration to hiclass using the following methods: - Platt Scaling - Isotonic Regression - Beta calibration - (Inductive/Cross) Venn-ABERS calibration

Added filtration and helper function what aims to make the interface more user-friendly

Hello, Is there a predict_proba() method for the LCPPN pipeline ??

Hi, Could you add a feature to the classifier in the form of a dictionary for classifiers trained locally on an LCPPN type classifier?

As of now, there is no functionality to update a classifier, one must recreate a new instance of the Hierarchical classifier. This PR adds a new method to update the...

**Is your feature request related to a problem? Please describe.** Many sklean models support partial_fit to allow tran models over big data. But this library does not support fit_partial for...

A / \ B C With the hiclass library, we can get the hierarchy [A,B] and [A, C] but can't get [A] only. Can you please look into this? Note-...