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

## TL;DR

ITree is a web-based tool for creating and modifying decision trees interactively, useful for analyzing biomedical data and teaching data classification.

## Contribution

ITree introduces interactive decision tree induction with real-time feedback and integrates Relative Expression Analysis for biomedical data exploration.

## Key findings

- ITree allows real-time updates of decision trees and their predictions.
- The tool supports manual, semi-automatic, and automatic tree induction.
- Relative Expression Analysis is incorporated for pattern detection in molecular data.

## Abstract

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.

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.

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