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HiClass: a Python library for local hierarchical classification compatible with scikit-learn

Fábio Malcher Miranda, Niklas Köhnecke, Bernhard Y. RenardPublished Dec 13, 2021
DOI Publisher
Researcher verdict
Context only
Use as context only
Benchmark evidence
Missing
Not verified yet
Time to first repro
A few days
Plan setup time
Risk flags
1
Review before use

Abstract

Domain fit: AI-adjacent · Paper appears method- or tooling-adjacent to AI workflows with partial ecosystem coverage.

HiClass is an open-source Python library for local hierarchical classification entirely compatible with scikit-learn. It contains implementations of the most common design patterns for hierarchical machine learning models found in the literature, that is, the local classifiers per node, per parent node and per level. Additionally, the package contains implementations of hierarchical metrics, which are more appropriate for evaluating classification performance on hierarchical data. The documentation includes installation and usage instructions, examples within tutorials and interactive notebooks, and a complete description of the API. HiClass is released under the simplified BSD license, encouraging its use in both academic and commercial environments. Source code and documentation are available at https://github.com/scikit-learn-contrib/hiclass.

Results and benchmarks

Freshness tier: cold
HiClass is an open-source Python library for local hierarchical classification entirely compatible with scikit-learn.

Implementation

No direct implementation yet

Maintained implementation evidence is not confirmed for this paper yet.

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Implementation evidence summary
Confidence: low

scikit-learn-contrib/hiclass is the closest maintained adjacent implementation (Strong overlap with paper title keywords). It is not paper-verified; validate algorithm and evaluation setup against the paper before trusting reported metrics. Community adoption signal: 138 GitHub stars.

Reproduction risks
  • Adjacent implementations are not paper-verified
  • Recommended repository is adjacent and not paper-verified.
  • Adjacent implementation match confidence is low.

Reproduction readiness

Time to first repro: days
Last checked: Aug 24, 2026

No repo

No verified implementation available

  • No maintained repository has been identified for this paper. Check adjacent implementations or HF artifacts below.

Hardware requirements

  • Expect multi-day setup/compute for meaningful reproduction based on current guidance.

Repositories and ecosystem

Closest related implementations

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Research context

21

Citations

0

References

Tasks

Python (programming language), Documentation, Computer science, Implementation, MIT License, License, Extensibility, Programming language

Methods

None detected

Domains

Biochemistry, Genetics and Molecular Biology

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