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» Combining Methods for Dynamic Multiple Classifier Systems
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122
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CATE
2004
190views Education» more  CATE 2004»
15 years 1 months ago
Enhancing Online Learning Performance: An Application of Data Mining Methods
Recently web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
FUZZIEEE
2007
IEEE
15 years 4 months ago
Ensembles of Fuzzy Classifiers
The use of bagging is explored to create an ensemble of fuzzy classifiers. The learning algorithm used was ANFIS (Adaptive Neuro-Fuzzy Inference Systems). We compare results from b...
Juana Canul-Reich, Larry Shoemaker, Lawrence O. Ha...
103
Voted
ICMCS
2010
IEEE
212views Multimedia» more  ICMCS 2010»
15 years 1 months ago
Homogeneous segmentation and classifier ensemble for audio tag annotation and retrieval
Audio tags describe different types of musical information such as genre, mood, and instrument. This paper aims to automatically annotate audio clips with tags and retrieve releva...
Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang
86
Voted
CVPR
2008
IEEE
16 years 2 months ago
Detection with multi-exit asymmetric boosting
We introduce a generalized representation for a boosted classifier with multiple exit nodes, and propose a method to training which combines the idea of propagating scores across ...
Minh-Tri Pham, V-D. D. Hoang, Tat-Jen Cham
98
Voted
ICONIP
2009
14 years 10 months ago
Probabilistic Combination of Multiple Evidence
In pattern recognition systems, data fusion is an important issue and evidence theory is one such method that has been successful. Many researchers have proposed different rules fo...
Heeyoul Choi, Anup Katake, Seungjin Choi, Yoonseop...