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classifiers

ruff check --select I --fix . && ruff format .

Expected input is features and labels columns.

task labels per example example
binary scalar 0/1 1
multilabel multi-hot list, length num_labels [1, 0, 1]
multiclass int class index 0..k-1 2

Multilabel must be multi-hot, not index lists. To convert [0, 2] → [1, 0, 1]:

def to_multihot(ex, k):
    v = [0.0] * k
    for i in ex["labels"]:
        v[i] = 1.0
    return {"labels": v}

ds = ds.map(to_multihot, fn_kwargs={"k": num_labels})

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Release files for classifiers 0.1.0

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Table of built distributions (wheels) for classifiers 0.1.0
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