Large Scale Learning Techniques for Least Squares Support Vector Machines

2019 ◽  
pp. 3-11
Author(s):  
Santiago Toledo-Cortés ◽  
Ivan Y. Castellanos-Martinez ◽  
Fabio A. Gonzalez
Keyword(s):  
Support Vector Machines ◽  
Least Squares ◽  
Large Scale ◽  
Support Vector ◽  
Large Scale Learning ◽  
Learning Techniques ◽  
Vector Machines

Large scale classification of spectral signatures

2015 ◽  
Vol 82 (12) ◽  
Author(s):  
Matthias Richter ◽  
Thomas Längle ◽  
Jürgen Beyerer
Keyword(s):  
Support Vector Machines ◽  
Least Squares ◽  
Partial Least Squares ◽  
Large Scale ◽  
Expert Knowledge ◽  
Pharmaceutical Products ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Vector Machines

AbstractHyperspectral sensors are becoming cheaper, faster and more readily available. Apart from industry applications, manufacturers push to bring compact devices into the end-consumer market. This development gives rise to many interesting applications such as the identification of counterfeit pharmaceutical products or the classification of food stuffs. These applications require precise models of the underlying classes. However, building these models from expert knowledge is not feasible. In this paper, we propose to use machine learning techniques to infer a model of many classes from an annotated dataset instead. We investigate the use of three popular methods: support vector machines, random forest classifiers and partial least squares. In contrast to similar approaches using support vector machines, we restrict ourselves to the linear formulation and train the classifiers by solving the primal, instead of dual optimization problem. Our experiments on a large dataset show that the support vector machine approach is superior to random forests and partial least squares in classification accuracy as well as training time.

Large-scale pinball twin support vector machines

2021 ◽  
Author(s):  
M. Tanveer ◽  
A. Tiwari ◽  
R. Choudhary ◽  
M. A. Ganaie
Keyword(s):  
Support Vector Machines ◽  
Large Scale ◽  
Support Vector ◽  
Twin Support Vector Machines ◽  
Vector Machines
Sign in / Sign up

Export Citation Format

Share Document