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Twin Support Vector Machine: A review from 2007 to 2014
Egyptian Informatics Journal, 2015 Twin Support Vector Machine (TWSVM) is an emerging machine learning method suitable for both classification and regression problems. It utilizes the concept of Generalized Eigen-values Proximal Support Vector Machine (GEPSVM) and finds two non-parallel ...
Divya Tomar, Sonali Agarwal
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Using bag-of-concepts to improve the performance of support vector machines in text categorization [PDF]
, 2004 This paper investigates the use of concept-based representations for text categorization. We introduce a new approach to create concept-based text representations, and apply it to a standard text categorization collection. The representations are used as
Cöster, Rickard, Sahlgren, Magnus
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Vector machine techniques for modeling of seismic liquefaction data
Ain Shams Engineering Journal, 2014 This article employs three soft computing techniques, Support Vector Machine (SVM); Least Square Support Vector Machine (LSSVM) and Relevance Vector Machine (RVM), for prediction of liquefaction susceptibility of soil.
Pijush Samui
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Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): an algorithm for joint optimization of discrimination and calibration. [PDF]
, 2012 Historically, probabilistic models for decision support have focused on discrimination, e.g., minimizing the ranking error of predicted outcomes. Unfortunately, these models ignore another important aspect, calibration, which indicates the magnitude of ...
Jiang, Xiaoqian +4 more
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Gaussian Pyramid for Nonlinear Support Vector Machine
Applied Computational Intelligence and Soft Computing, 2022 Support vector machine (SVM) is one of the most efficient machine learning tools, and it is fast, simple to use, reliable, and provides accurate classification results.
Rawan Abo Zidan, George Karraz
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Hierarchical linear support vector machine [PDF]
, 2012 This is the author’s version of a work that was accepted for publication in Pattern Recognition. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not
Huerta, Ramón +2 more
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The Stata Journal: Promoting communications on statistics and Stata, 2016 Support vector machines are statistical- and machine-learning techniques with the primary goal of prediction. They can be applied to continuous, binary, and categorical outcomes analogous to Gaussian, logistic, and multinomial regression. We introduce a new command for this purpose, svmachines.
Nick Guenther, Matthias Schonlau
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$$\nu $$ ν -Improved nonparallel support vector machine
Scientific Reports, 2022 In this paper, a $$\nu $$ ν -improved nonparallel support vector machine ( $$\nu $$ ν -IMNPSVM) is proposed to solve binary classification problems.
Fengmin Sun, Shujun Lian
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Multitraining support vector machine for image retrieval [PDF]
, 2006 Relevance feedback (RF) schemes based on support vector machines (SVMs) have been widely used in content-based image retrieval (CBIR). However, the performance of SVM-based RF approaches is often poor when the number of labeled feedback samples is small.
Allinson, N. +3 more
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Penerapan Metode Support Vector Machine pada Sistem Deteksi Intrusi secara Real-time [PDF]
, 2013 Intrusion detection system is a system for detecting attacks or intrusions in a network or computer system, generally intrusion detection is done with comparing network traffic pattern with known attack pattern or with finding unnormal pattern of network
Jacobus, J. (Jacobus), Winarko, E. (Edi)
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