Learn machine learning from the ground up - using Python and a handful of fundamental tools. This repository contains a range of resources associated with the 2nd edition of the university textbook ...

Abstract: This paper presents a comprehensive fault classification framework for three-phase Induction Motors (IMs) using a novel Grey Wolf Optimization-enhanced Support Vector Machine (GWO-SVM) ...

Abstract: The rapid adoption of Electric Vehicles (EVs) necessitates advanced solutions for flexible charging (FC) systems to meet diverse user needs and optimize grid efficiency. This study ...

To compare the comprehensive performance of conventional logistic regression (LR) and seven machine learning (ML) algorithms in Noise-Induced Hearing Loss (NIHL) prediction, and to investigate the ...

Monitoring nociception, the flow of information associated with harmful stimuli through the nervous system even during unconsciousness, is critical for proper anesthesia care during surgery. Currently ...

This study investigated whether machine learning (ML) has better predictive accuracy than logistic regression analysis (LR) for gait independence at discharge in subacute stroke patients (n = 843) who ...

This short course focuses on understanding the principles of logistic regression using the notions of odds, odds ratios and transformations. It includes discussion of how good the given model is, and ...

Dataset import and preprocessing Automatic feature map generation 27-type feature catalogue for iterative (re)calculation to support model integration into optimization 7 customizable internal model ...

Department of Chemical Engineering, Imperial College London, London SW7 2AZ, U.K. Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Çengelköy, Istanbul 34684, Turkey Department of ...

Traditionally, mathematical models have been applied to describe growth-age relationship in animals. One important feature of these models is their ability to describe the weight gain and evaluate ...