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» Combining Classifiers based on Confidence Values
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FUZZIEEE
2007
IEEE
13 years 10 months ago
Evolving Single- and Multi-Model Fuzzy Classifiers with FLEXFIS-Class
Abstract-- In this paper a new method for training singlemodel and multi-model fuzzy classifiers incrementally and adaptively is proposed, which is called FLEXFIS-Class. The evolvi...
Edwin Lughofer, Plamen P. Angelov, Xiaowei Zhou
MLDM
2008
Springer
13 years 6 months ago
Classification Based on Consistent Itemset Rules
Abstract. We propose an approach to build a classifier composing consistent (100% confident) rules. Recently, associative classifiers that utilize association rules have been widel...
Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura
RSFDGRC
2007
Springer
236views Data Mining» more  RSFDGRC 2007»
14 years 11 days ago
Constructing Associative Classifier Using Rough Sets and Evidence Theory
Constructing accurate classifier based on association rule is an important and challenging task in data mining. In this paper, a novel combination strategy based on rough sets (RST...
Yuan-Chun Jiang, Ye-Zheng Liu, Xiao Liu, Jie-Kui Z...
SDM
2010
SIAM
218views Data Mining» more  SDM 2010»
13 years 7 months ago
Confidence-Based Feature Acquisition to Minimize Training and Test Costs
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...
CVIU
2004
152views more  CVIU 2004»
13 years 6 months ago
Detecting image orientation based on low-level visual content
Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection al...
Yongmei Michelle Wang, HongJiang Zhang