Support vector machine in machine condition monitoring and fault diagnosis

A Widodo, BS Yang - Mechanical systems and signal processing, 2007 - Elsevier
Recently, the issue of machine condition monitoring and fault diagnosis as a part of
maintenance system became global due to the potential advantages to be gained from …

A geometric approach to support vector machine (SVM) classification

ME Mavroforakis, S Theodoridis - IEEE transactions on neural …, 2006 - ieeexplore.ieee.org
The geometric framework for the support vector machine (SVM) classification problem
provides an intuitive ground for the understanding and the application of geometric …

Class imbalance learning using fuzzy ART and intuitionistic fuzzy twin support vector machines

S Rezvani, X Wang - Information Sciences, 2021 - Elsevier
The classification in imbalanced datasets is one of the main problems for machine learning
techniques. Support vector machine (SVM) is biased to the majority class samples, and the …

A ν-twin support vector machine (ν-TSVM) classifier and its geometric algorithms

X Peng - Information Sciences, 2010 - Elsevier
In this paper, a ν-twin support vector machine (ν-TSVM) is presented, improving upon the
recently proposed twin support vector machine (TSVM). This ν-TSVM introduces a pair of …

[PDF][PDF] Statistical pattern recognition toolbox for Matlab

V Franc, V Hlavác - Prague, Czech: Center for Machine Perception …, 2004 - 147.32.84.2
The Statistical Pattern Recognition Toolbox (abbreviated STPRtool) is a collection of pattern
recognition (PR) methods implemented in Matlab. The core of the STPRtool is comprised of …

Finding optimal model parameters by discrete grid search

ÁB Jiménez, JL Lázaro, JR Dorronsoro - Innovations in hybrid intelligent …, 2008 - Springer
Finding optimal parameters for a model is usually a crucial task in engineering approaches
to classification and modeling tasks. An automated approach is particularly desirable when …

A distributed support vector machine learning over wireless sensor networks

W Kim, MS Stanković, KH Johansson… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
This paper is about fully-distributed support vector machine (SVM) learning over wireless
sensor networks. With the concept of the geometric SVM, we propose to gossip the set of …

A modified support vector machine and its application to image segmentation

Z Yu, HS Wong, G Wen - Image and Vision Computing, 2011 - Elsevier
Recently, researchers are focusing more on the study of support vector machine (SVM) due
to its useful applications in a number of areas, such as pattern recognition, multimedia …

Efficient twin parametric insensitive support vector regression model

X Peng - Neurocomputing, 2012 - Elsevier
In this paper, an efficient twin parametric insensitive support vector regression (TPISVR) is
proposed. The TPISVR determines indirectly the regression function through a pair of …

Machine learning algorithm based on convex hull analysis

AP Nemirko, JH Dulá - Procedia Computer Science, 2021 - Elsevier
In this paper machine learning methods for automatic classification problems using
computational geometry are considered. Classes are defined with convex hulls of points …