problexity—An open-source Python library for supervised learning problem complexity assessment

The problem’s complexity assessment is an essential element of many topics in the supervised learning domain. It plays a significant role in meta-learning – becoming the basis for determining meta-attributes or multi-criteria optimization – allowing the evaluation of the training set resampling with...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Neurocomputing (Amsterdam) Jg. 521; S. 126 - 136
Hauptverfasser: Komorniczak, Joanna, Ksieniewicz, Paweł
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 07.02.2023
Schlagworte:
Classification
Problem complexity
Python
Regression
Regression
Problem complexity
Classification
Python
ISSN:0925-2312, 1872-8286
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The problem’s complexity assessment is an essential element of many topics in the supervised learning domain. It plays a significant role in meta-learning – becoming the basis for determining meta-attributes or multi-criteria optimization – allowing the evaluation of the training set resampling without needing to rebuild the recognition model. The tools currently available for the academic community, which would enable the calculation of problem complexity measures, are available only as libraries of the C++ and R languages. This paper describes the software module that allows for the estimation of 22 classification complexity measures and 12 regression complexity measures for the Python language – compatible with the scikit-learn programming interface – allowing for the implementation of research using them in the most popular programming environment of the machine learning community.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2022.11.056