A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Highly detailed 3D scans of dense tropical rain forest plots are enabling precise estimates of tree structure, volume and ...

Abstract: Machine learning has been successfully applied to drug combination prediction in recent years. However, in some situations, the class imbalance problem still shows highly negative impacts on ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Urban landscapes could be cooled by up to 3.5 degrees using a QUT-developed AI-based tool that optimizes where trees and which species are planted to make cities cooler, greener and more resilient in ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Decision trees are among the most interpretable models in machine learning, widely valued for their transparency, simplicity, and alignment with human reasoning. However, traditional decision tree ...

This paper first discusses the storage structure of trees, selects a convenient storage method for solving the nullity of trees, and then applies the relationship between the maximum matching number ...

WEST LAFAYETTE, Ind. — Trees compete for space as they grow. A tree with branches close to a wall will develop differently from one growing on open ground. Now everyone from urban planners and ...