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» Combining Methods for Dynamic Multiple Classifier Systems
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99
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MCS
2000
Springer
15 years 1 months ago
Analysis of a Fusion Method for Combining Marginal Classifiers
The use of multiple features by a classifier often leads to a reduced probability of error, but the design of an optimal Bayesian classifier for multiple features is dependent on t...
Mark D. Happel, Peter Bock
CIARP
2007
Springer
15 years 3 months ago
Confusion Matrix Disagreement for Multiple Classifiers
We present a methodology to analyze Multiple Classifiers Systems (MCS) performance, using the disagreement concept. The goal is to define an alternative approach to the conventiona...
Cinthia Obladen de Almendra Freitas, João M...
78
Voted
DAS
2006
Springer
15 years 1 months ago
Combining Multiple Classifiers for Faster Optical Character Recognition
Traditional approaches to combining classifiers attempt to improve classification accuracy at the cost of increased processing. They may be viewed as providing an accuracy-speed tr...
Kumar Chellapilla, Michael Shilman, Patrice Simard
71
Voted
FSKD
2006
Springer
124views Fuzzy Logic» more  FSKD 2006»
15 years 1 months ago
An Effective Combination of Multiple Classifiers for Toxicity Prediction
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...
Gongde Guo, Daniel Neagu, Xuming Huang, Yaxin Bi
79
Voted
FLAIRS
2000
14 years 11 months ago
Overriding the Experts: A Stacking Method for Combining Marginal Classifiers
The design of an optimal Bayesian classifier for multiple features is dependent on the estimation of multidimensional joint probability density functions and therefore requires a ...
Mark D. Happel, Peter Bock