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» Unsupervised Classifier Selection Based on Two-Sample Test
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CIARP
2006
Springer
15 years 3 months ago
Feature Selection Based on Mutual Correlation
Feature selection is a critical procedure in many pattern recognition applications. There are two distinct mechanisms for feature selection namely the wrapper methods and the filte...
Michal Haindl, Petr Somol, Dimitrios Ververidis, C...
IPMI
2003
Springer
16 years 16 days ago
Feature Selection for Shape-Based Classification of Biological Objects
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...
CCS
2007
ACM
15 years 5 months ago
Defining categories to select representative attack test-cases
To ameliorate the quality of protection provided by intrusion detection systems (IDS) we strongly need more effective evaluation and testing procedures. Evaluating an IDS against ...
Mohammed S. Gadelrab, Anas Abou El Kalam, Yves Des...
DRR
2008
15 years 1 months ago
Whole-book recognition using mutual-entropy-driven model adaptation
We describe an approach to unsupervised high-accuracy recognition of the textual contents of an entire book using fully automatic mutual-entropy-based model adaptation. Given imag...
Pingping Xiu, Henry S. Baird
ESWA
2008
134views more  ESWA 2008»
14 years 10 months ago
Neighborhood classifiers
K nearest neighbor classifier (K-NN) is widely discussed and applied in pattern recognition and machine learning, however, as a similar lazy classifier using local information for...
Qinghua Hu, Daren Yu, Zongxia Xie