BIOENGINEER

Entropy-weighted feature selection lifts heart disease prediction to 94 percent accuracy

A new entropy-weighted feature selection method trims 13 clinical attributes down to 8 and pushes heart disease prediction ...
BIOENGINEER

Self-Distilled Graph Learning Tames Noisy Labels in Multi-Label Feature Selection

Researchers have introduced SDMFS, a unified framework combining self-distillation and adaptive label graph learning that ...
Nature

Feature Selection Techniques in Machine Learning Systems articles from across Nature Portfolio

Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains ...
techtarget

How feature selection, extraction improve ML predictions

This article is excerpted from the course "Fundamental Machine Learning," part of the Machine Learning Specialist certification program from Arcitura Education. It is the sixth part of the 13-part ...