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» Fusion of multiple classifiers
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KBS
2006
79views more  KBS 2006»
13 years 8 months ago
Using multiple and negative target rules to make classifiers more understandable
One major goal for data mining is to understand data. Rule based methods are better than other methods in making mining results comprehensible. However, the current rule based cla...
Jiuyong Li, Jason Jones
JMLR
2006
135views more  JMLR 2006»
13 years 8 months ago
Statistical Comparisons of Classifiers over Multiple Data Sets
While methods for comparing two learning algorithms on a single data set have been scrutinized for quite some time already, the issue of statistical tests for comparisons of more ...
Janez Demsar
CIARP
2007
Springer
14 years 2 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...
DAS
2006
Springer
14 years 10 days 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
ICPR
2010
IEEE
14 years 2 days ago
Inverse Multiple Instance Learning for Classifier Grids
Abstract--Recently, classifier grids have shown to be a considerable alternative for object detection from static cameras. However, one drawback of such approaches is drifting if a...
Sabine Sternig, Peter M. Roth, Horst Bischof