The increasing interest in Support Vector Machines (SVMs) over the past 15 years is
described. Methods are illustrated using simulated case studies, and 4 experimental case …

Predicting student academic performance has long been an important research topic in
many academic disciplines. The present study is the first study that develops and compares …

Pulmonary auscultation is essential for detecting abnormal lung sounds during physical
assessments, but its reliability depends on the operator. Machine learning (ML) models offer …

The foundations of Support Vector Machines (SVM) have been developed by Vapnik [19]
and are gaining popularity due to many attractive features, and promising empirical …

针对地下水系统结构不甚清晰, 基础资料不完备条件下区域地下水位预报问题,
在介绍支持向量机基本原理和实现算法的基础上, 探讨了支持向量机方法在区域地下水位预报中 …

By using relevance feedback, content-based image retrieval (CBIR) allows the user to
retrieve images interactively. Beginning with a coarse query, the user can select the most …

Support vector machine (SVM) is a new learning method developed in recent years based
on the foundations of statistical learning theory. By taking a transductive approach instead of …

Multichannel EEG data processing is usually required to decode Motor Imagery (MI) specific
cognitive patterns in Brain-Computer Interface (BCI) systems. The signals from its channels …

Abstract Support Vector Machines using ANOVA Decomposition Kernels (SVAD)[Vapng] are
a way of imposing a structure on multi-dimensional kernels which are generated as the …