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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 …
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 …
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
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 …
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 …
recently proposed twin support vector machine (TSVM). This ν-TSVM introduces a pair of …
[PDF][PDF] Statistical pattern recognition toolbox for Matlab
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 …
recognition (PR) methods implemented in Matlab. The core of the STPRtool is comprised of …
Finding optimal model parameters by discrete grid search
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 …
to classification and modeling tasks. An automated approach is particularly desirable when …
A distributed support vector machine learning over wireless sensor networks
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 …
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
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 …
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 …
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 …
computational geometry are considered. Classes are defined with convex hulls of points …