Tag: feature selection

Researchers evaluated six machine learning models on a twelve-month groundwater dataset from Uyo, Nigeria, demonstrating that penalized linear regression perfectly ...

A study of community-based chronic obstructive pulmonary disease patients found that an interpretable logistic regression model using six clinical predictors ...

Researchers introduced MedChain, an AI-powered framework combining blockchain, custom encryption, and machine learning algorithms to protect sensitive personal health records ...

A machine learning framework combining empirical Fourier decomposition and dragonfly feature selection detected cognitive load from electroencephalogram signals with high ...

Researchers developed PCLPred, a support vector machine model integrating reduced amino acid alphabets and tripeptide composition to identify plant chloride ...

Computer scientists evaluated Boruta, Recursive Feature Elimination, and Lasso feature selection across eight machine learning algorithms to classify encrypted darknet ...

A combined local search and genetic algorithm improved cancer classification accuracy and reduced computational complexity across more than 30,000 patient ...

Researchers have developed an explainable hybrid intrusion detection framework that combines data balancing, statistical feature selection, and ensemble learning to ...

A deep learning framework using Swin Transformer feature extraction and feature selection achieved 98.31 percent accuracy in diagnosing multi-class skin ...

A systematic evaluation shows that feature selection performance in multiclass biomedical classification is highly dataset-dependent, with SHAP excelling on eco-medical ...