iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://jmlr.org/papers/v24/21-1518.html
HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn



Home Page

Papers

Submissions

News

Editorial Board

Special Issues

Open Source Software

Proceedings (PMLR)

Data (DMLR)

Transactions (TMLR)

Search

Statistics

Login

Frequently Asked Questions

Contact Us



RSS Feed

HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn

Fábio M. Miranda, Niklas Köhnecke, Bernhard Y. Renard; 24(29):1−17, 2023.

Abstract

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.

[abs][pdf][bib]        [code]
© JMLR 2023. (edit, beta)

Mastodon