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» Classifier Combining Rules Under Independence Assumptions
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ISBI
2004
IEEE
14 years 7 months ago
Performance-Based Multi-Classifier Decision Fusion for Atlas-Based Segmentation of Biomedical Images
Combinations of multiple classifiers have been found to be consistently more accurate than a single classifier. The construction of multiple independent classifiers, however, is t...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
BMCBI
2006
129views more  BMCBI 2006»
13 years 6 months ago
Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials
Background: Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied t...
Tomasz G. Smolinski, Roger Buchanan, Grzegorz M. B...
DIS
2004
Springer
13 years 10 months ago
Maximum a Posteriori Tree Augmented Naive Bayes Classifiers
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
Jesús Cerquides, Ramon López de M&aa...
IJAR
2002
109views more  IJAR 2002»
13 years 6 months ago
Belief function independence: I. The marginal case
In this paper, we study the notion of marginal independence between two sets of variables when uncertainty is expressed by belief functions as understood in the context of the tra...
Boutheina Ben Yaghlane, Philippe Smets, Khaled Mel...
ICML
2003
IEEE
14 years 7 months ago
Tractable Bayesian Learning of Tree Augmented Naive Bayes Models
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
Jesús Cerquides, Ramon López de M&aa...