Per-label classifier

Description

Contributor guide

Tech stack

pythonscikit learn

Domain

machine learning

Issue type

feature

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

3

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

1-2 days

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

active

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

mostly clear

Prerequisites

Familiarity with scikit learn's MultiOutputClassifierUnderstanding of River's base estimator API

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

50

Research direction

Study scikit learn's MultiOutputClassifier implementation and River's existing multi output support. Look at River's base classifier API and existing classes like `metrics` or `utils` to understand how to wrap per label classifiers. Review the linked issue comments for any additional context or requirements.