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» On reoptimizing multi-class classifiers
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ICPR
2004
IEEE
9 years 4 months ago
Multi-Class Extensions of the GLDB Feature Extraction Algorithm for Spectral Data
The Generalized Local Discriminant Bases (GLDB) algorithm proposed by Kumar, Ghosh and Crawford in [4], is a effective feature extraction method for spectral data. It identifies g...
Pavel Paclík, Robert P. W. Duin, Serguei Ve...
ICAI
2010
8 years 1 months ago
Using Sensor Sequences for Activity Recognition by Mining and Multi-Class Adaboost
- In this paper, we present an activity recognition system using sensor sequence information generated from many binary on-off state sensors. When many sensors are deployed the num...
Md. Kamrul Hasan, Sungyoung Lee, Young-Koo Lee
ML
2008
ACM
101views Machine Learning» more  ML 2008»
8 years 3 months ago
On reoptimizing multi-class classifiers
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
PAA
2002
8 years 2 months ago
Combining Discriminant Models with New Multi-Class SVMs
: The idea of performing model combination, instead of model selection, has a long theoretical background in statistics. However, making use of theoretical results is ordinarily su...
Yann Guermeur
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