Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...

A decision tree classifier is a machine learning (ML) prediction system that generates rules such as "IF income < 28.0 AND education >= 14.0 THEN politicalParty = 2." Using a decision tree classifier ...

Clinical Relevance of Noncoding Adenosine-to-Inosine RNA Editing in Multiple Human Cancers In total, 60 CDTs were necessary to cover the whole guideline and were driven by 114 data items. Data items ...

Discover how random forests, a machine-learning technique, enhance prediction accuracy by combining insights from multiple ...

The cotton bollworm, Helicoverpa armigera (Hϋbner) is one of the most important pests affecting crop production globally. The data-mining technique, for predicting pest incidence using biotic and ...

Objective The objective was to examine the 22 variables from the Sport Concussion Assessment Tool’s 5 th Edition (SCAT5) Symptom Evaluation using a decision tree analysis to identify those most likely ...