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» Support vector machine via nonlinear rescaling method
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JMLR
2006
131views more  JMLR 2006»
13 years 7 months ago
On Representing and Generating Kernels by Fuzzy Equivalence Relations
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Bernhard Moser
CIS
2005
Springer
14 years 24 days ago
MFCC and SVM Based Recognition of Chinese Vowels
Abstract. The recognition of vowels in Chinese speech is very important for Chinese speech recognition and understanding. However, it is rather difficult and there has been no effi...
Fuhai Li, Jinwen Ma, Dezhi Huang
BMCBI
2007
96views more  BMCBI 2007»
13 years 7 months ago
Protein subcellular localization prediction based on compartment-specific features and structure conservation
Motivation: Protein subcellular localization is crucial for genome annotation, protein function prediction, and drug discovery. However, since determining subcellular localization...
Emily Chia-Yu Su, Hua-Sheng Chiu, Allan Lo, Jenn-K...
ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 7 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
IJCAI
2007
13 years 8 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans