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ICANN
2007
Springer
14 years 1 months ago
Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
Shigeo Abe, Kenta Onishi
ICDM
2005
IEEE
135views Data Mining» more  ICDM 2005»
14 years 1 months ago
Bit Reduction Support Vector Machine
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
INFORMATICALT
2007
111views more  INFORMATICALT 2007»
13 years 7 months ago
Oblique Support Vector Machines
In this paper we propose a modified framework of support vector machines, called Oblique Support Vector Machines(OSVMs), to improve the capability of classification. The principl...
Chih-Chia Yao, Pao-Ta Yu
ICDM
2008
IEEE
99views Data Mining» more  ICDM 2008»
14 years 2 months ago
Kernels for the Investigation of Localized Spatiotemporal Transitions of Drought with Support Vector Machines
We present and discuss several spatiotemporal kernels designed to mine real-life and simulated data in support of drought prediction. We implement and empirically validate these k...
Matthew W. Collier, Amy McGovern
SIGIR
2004
ACM
14 years 29 days ago
Classifying racist texts using a support vector machine
In this poster we present an overview of the techniques we used to develop and evaluate a text categorisation system for the PRINCIP project which sets out to automatically classi...
Edel Greevy, Alan F. Smeaton