Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

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

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Abstract: Feature selection is a pivotal step in machine learning, aimed at reducing feature dimensionality and improving model performance. Conventional feature selection methods, typically framed as ...

This repository contains the implementation of the granular ball-based feature selection algorithm for multi-label learning, as described in the research paper published in Knowledge-Based Stems. Note ...

Abstract: Fuzzy rough feature selection (FRFS) effectively alleviates the curse of dimensionality by eliminating redundant and irrelevant features, thereby improving model generalization. However, ...