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» Optimal feature selection for support vector machines
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IJON
2006
146views more  IJON 2006»
13 years 7 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
ICMCS
2005
IEEE
129views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Feature Selection and Stacking for Robust Discrimination of Speech, Monophonic Singing, and Polyphonic Music
In this work we strive to find an optimal set of acoustic features for the discrimination of speech, monophonic singing, and polyphonic music to robustly segment acoustic media st...
Björn Schuller, Brüning J. B. Schmitt, D...
IJCNN
2007
IEEE
14 years 2 months ago
Evaluation of Performance Measures for SVR Hyperparameter Selection
— To obtain accurate modeling results, it is of primal importance to find optimal values for the hyperparameters in the Support Vector Regression (SVR) model. In general, we sea...
Koen Smets, Brigitte Verdonk, Elsa Jordaan
ICML
2010
IEEE
13 years 9 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
ICASSP
2011
IEEE
12 years 11 months ago
Effective background data selection in SVM speaker recognition for unseen test environment: More is not always better
This study focuses on determining a procedure to select effective negative examples for development of improved Support Vector Machine (SVM) based speaker recognition. Selection o...
Jun-Won Suh, Yun Lei, Wooil Kim, John H. L. Hansen