Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...

Department of Chemistry, University of Washington, Seattle, Washington 98195-1700, United States ...

Abstract: The work's objective is to assess how well the classification techniques of logistic regression and support vector machine predict handwritten digits. A Digit dataset with 985 records is ...

ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...

Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...