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» Data selection for support vector machine classifiers
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SIGIR
2005
ACM
15 years 3 months ago
A phonotactic-semantic paradigm for automatic spoken document classification
We demonstrate a phonotactic-semantic paradigm for spoken document categorization. In this framework, we define a set of acoustic words instead of lexical words to represent acous...
Bin Ma, Haizhou Li
IJCNN
2000
IEEE
15 years 2 months ago
Support Vector Machines Based on a Semantic Kernel for Text Categorization
We propose to solve a text categorization task using a new metric between documents, based on a priori semantic knowledge about words. This metric can be incorporated into the def...
George Siolas, Florence d'Alché-Buc
EMO
2009
Springer
147views Optimization» more  EMO 2009»
15 years 4 months ago
Application of MOGA Search Strategy to SVM Training Data Selection
When training Support Vector Machine (SVM), selection of a training data set becomes an important issue, since the problem of overfitting exists with a large number of training da...
Tomoyuki Hiroyasu, Masashi Nishioka, Mitsunori Mik...
CIBCB
2005
IEEE
15 years 3 months ago
Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
DATAMINE
1998
145views more  DATAMINE 1998»
14 years 9 months ago
A Tutorial on Support Vector Machines for Pattern Recognition
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-...
Christopher J. C. Burges