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 ...
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 ...
Nature

Feature Selection Techniques in Machine Learning Systems

Feature selection is a critical pre-processing step in machine learning that seeks to identify a subset of input variables most relevant to predictive modelling. By reducing dimensionality, it ...
News Medical

New machine learning model achieves breakthrough in heart disease prediction with over 95% accuracy

In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...
InfoWorld

Machine learning: Demystifying linear regression and feature selection

Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems can ...