The Data Science Lab Multi-Class Classification Using a scikit Decision Tree Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the ...

The Data Science Lab Binary Classification Using a scikit Decision Tree Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained ...

Supervised learning is a machine learning approach in which algorithms are trained on labelled datasets—that is, data that already includes the correct outputs or classifications. The model learns to ...

The visual data mining process, seen in the first part of this two-part article, revealed patterns in four dimensions between cumulative gas well production and independent variables ...

Once an algorithm is trained on massive datasets to recognize patterns, make decisions, and generate insights, it becomes an AI model. The more data it has been trained on, the more accurate it is.

Additionally, we aim to investigate risk factors associated with the incidence of CIPN within the local context using the classification and regression tree (CART) algorithm, which yields an easily ...

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, ...