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KAIS
2006
121views more  KAIS 2006»
15 years 4 months ago
Using discriminant analysis for multi-class classification: an experimental investigation
Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
Tao Li, Shenghuo Zhu, Mitsunori Ogihara
KDD
1995
ACM
139views Data Mining» more  KDD 1995»
15 years 7 months ago
Extracting Support Data for a Given Task
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
Bernhard Schölkopf, Chris Burges, Vladimir Va...
IPM
2008
159views more  IPM 2008»
15 years 4 months ago
Exploring syntactic structured features over parse trees for relation extraction using kernel methods
Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This ...
Min Zhang, Guodong Zhou, AiTi Aw
TCS
2008
15 years 4 months ago
Kernel methods for learning languages
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
16 years 1 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...