Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily interpretable, but often don't work well with large ...

A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A multi-class classification problem is one where the goal is to predict the ...

Algorithms define the rules, conditions, and methodology that an AI will use when processing and analyzing data. Written by eWEEK content and product recommendations are editorially independent. We ...

Objective: To determine whether classification tree techniques used on survey data collected at enrollment from older adults in a Medicare HMO could predict the likelihood of an individual being in a ...

This article considers a measure of variable importance frequently used in variable-selection methods based on decision trees and tree-based ensemble models. These models include CART, random forests, ...

Motivated by this need, this work rigorously evaluates the performance of three ML algorithms: Decision Trees, Logistic Regression, and K-Nearest Neighbors (KNN) to accurately assess their robustness ...