ITree: a user-driven tool for interactive decision-making with classification trees

Hubert Sokołowski; Marcin Czajkowski; Anna Czajkowska; Krzysztof Jurczuk; Marek Kretowski

doi:10.1093/bioinformatics/btae273

ITree: a user-driven tool for interactive decision-making with classification trees

Bioinformatics. 2024 Apr 18:btae273. doi: 10.1093/bioinformatics/btae273. Online ahead of print.

Authors

Hubert Sokołowski¹, Marcin Czajkowski¹, Anna Czajkowska^{2

3}, Krzysztof Jurczuk¹, Marek Kretowski¹

Affiliations

¹ Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland.
² Department Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland.
³ Department of Medical Biology, Medical University of Bialystok, Poland.

PMID: 38640482
DOI: 10.1093/bioinformatics/btae273

Abstract

Motivation: ITree is an intuitive web tool for the manual, semi-automatic, and automatic induction of decision trees. It enables interactive modifications of tree structures and incorporates Relative Expression Analysis for detecting complex patterns in high-throughput molecular data. This makes ITree a versatile tool for both research and education in biomedical data analysis.

Results: The tool allows users to instantly see the effects of modifications on decision trees, with updates to predictions and statistics displayed in real time, facilitating a deeper understanding of data classification processes.

Availability and implementation: Available online at https://itree.wi.pb.edu.pl. Source code and documentation are hosted on GitHub at https://github.com/hsokolowski/iTree.

Supplementary information: Additional resources are provided to enhance user experience and support.