DOC fix the strategy used for multiclass in IHT #1013
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solegalli
reviewed
Jul 10, 2023
| Supports multi-class resampling. A one-vs.-rest scheme is used when | ||
| sampling a class as proposed in [1]_. | ||
| Supports multi-class resampling. We will go through each individual class to select | ||
| the samples with the highest probability to be correctly classified. |
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I'd rephrase like this:
Supports multi-class resampling: from each class to be under-sampled, it retains the observations with the highest probability of being correctly classified.
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I rephrase an pushed in master.
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closes #848
Update the docstring regarding the multiclass approach used in IHT. We don't use one vs. rest. Instead, we filter samples based on their classes and the assigned probabilities of a learner.