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KAIS
2006
121views more  KAIS 2006»
14 years 10 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
PAA
2002
14 years 10 months ago
Hierarchical Fusion of Multiple Classifiers for Hyperspectral Data Analysis
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...
Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford
CSDA
2008
128views more  CSDA 2008»
14 years 10 months ago
Classification tree analysis using TARGET
Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
J. Brian Gray, Guangzhe Fan
BMVC
2010
14 years 8 months ago
Multi-class Boosting for Early Classification of Sequences
We propose a new boosting algorithm for sequence classification, in particular one that enables early classification of multiple classes. In many practical problems, we would like...
Katsuhiko Ishiguro, Hiroshi Sawada, Hitoshi Sakano
JMLR
2010
143views more  JMLR 2010»
14 years 5 months ago
Rademacher Complexities and Bounding the Excess Risk in Active Learning
Sequential algorithms of active learning based on the estimation of the level sets of the empirical risk are discussed in the paper. Localized Rademacher complexities are used in ...
Vladimir Koltchinskii