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» On reoptimizing multi-class classifiers
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ICPR
2004
IEEE
16 years 1 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
14 years 10 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
105
Voted
ML
2008
ACM
101views Machine Learning» more  ML 2008»
15 years 9 days 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...
146
Voted
EUSFLAT
2009
679views Fuzzy Logic» more  EUSFLAT 2009»
14 years 10 months ago
Combining Wavelets and Computational Intelligence Methods with Applications on Multi-class Classification Datasets
In this paper, we propose a novel algorithm for wavelet feature extraction as input to a supervised Multi-Class Classifier to improve classification performance. In particular, to ...
Carlos Campos Bracho