Research Topic · Peer-Reviewed

Decision Trees

Decision trees are a type of predictive algorithm used for classification and regression problems. They are based on a tree-like structure of decisions, with each node representing a test of the values of an attribute, and each branch representing the outcome of the test. This structure makes decision trees easy to …

Curated from this journal's research 📚 5 peer-reviewed articles cited Cited 39× across the literature 🔖 ISSN 2768-0207 🗓 Reviewed June 2026

Overview

Decision trees are a type of predictive algorithm used for classification and regression problems. They are based on a tree-like structure of decisions, with each node representing a test of the values of an attribute, and each branch representing the outcome of the test. This structure makes decision trees easy to interpret and visualize, as well as providing good performance on large datasets. Decision trees can be used to solve many different types of problems such as classification, regression, forecasting and optimization. They can be used to identify patterns in data and help make decisions that are based on those patterns. Additionally, they are robust to outliers, non-linearity, and missing values. Their predictive accuracy and interpretability make them a valuable tool in a variety of applications, such as healthcare, financial services, and marketing.

Research published in this journal

5 peer-reviewed articles, ranked by relevance. Each links to its DOI.

How this research is being cited

The 5 articles above have been cited 39 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.

A sample of recent works citing this journal's research on Decision Trees, linking to each citing work.

Editorial oversight

Curated from peer-reviewed research published in Big Data Research (ISSN 2768-0207).

Journal editorial board
Professor Shangming Zhou · United Kingdom Professor Hong Lin · United States Dr. Rami H. Al-Rifai · United Arab Emirates

This page summarises published research for orientation; it is not medical or professional advice.