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» Experiments with Classifier Combining Rules
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RSFDGRC
2007
Springer
236views Data Mining» more  RSFDGRC 2007»
15 years 7 months 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...
ICPR
2002
IEEE
16 years 2 months ago
Combining SVM Classifiers for Handwritten Digit Recognition
In this paper, we investigate the advantages and weaknesses of various decision fusion schemes using statistical and rule-based reasoning. The cooperation schemes are applied on t...
Dejan Gorgevik, Dusan Cakmakov
ICPR
2002
IEEE
15 years 6 months ago
Analysis of Error-Reject Trade-off in Linearly Combined Classifiers
In this paper, a framework for the analysis of the error-reject trade-off in linearly combined classifiers is proposed. We start from a framework developed by Tumer and Ghosh [1,2...
Fabio Roli, Giorgio Fumera, Gianni Vernazza
ICML
2006
IEEE
16 years 2 months ago
Using query-specific variance estimates to combine Bayesian classifiers
Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a nov...
Chi-Hoon Lee, Russell Greiner, Shaojun Wang
SSPR
2000
Springer
15 years 4 months ago
The Role of Combining Rules in Bagging and Boosting
To improve weak classifiers bagging and boosting could be used. These techniques are based on combining classifiers. Usually, a simple majority vote or a weighted majority vote are...
Marina Skurichina, Robert P. W. Duin