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» Unsupervised Classifier Selection Based on Two-Sample Test
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DIS
2008
Springer
13 years 6 months ago
Unsupervised Classifier Selection Based on Two-Sample Test
We propose a well-founded method of ranking a pool of m trained classifiers by their suitability for the current input of n instances. It can be used when dynamically selecting a s...
Timo Aho, Tapio Elomaa, Jussi Kujala
DAC
2008
ACM
14 years 5 months ago
Functional test selection based on unsupervised support vector analysis
Extensive software-based simulation continues to be the mainstream methodology for functional verification of designs. To optimize the use of limited simulation resources, coverag...
Onur Guzey, Li-C. Wang, Jeremy R. Levitt, Harry Fo...
ICPR
2004
IEEE
14 years 6 months ago
A Consistency-Based Model Selection for One-Class Classification
Model selection in unsupervised learning is a hard problem. In this paper a simple selection criterion for hyperparameters in one-class classifiers (OCCs) is proposed. It makes us...
David M. J. Tax, Klaus-Robert Müller
TNN
2010
143views Management» more  TNN 2010»
12 years 11 months ago
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
SSPR
2000
Springer
13 years 8 months ago
Selection of Classifiers Based on Multiple Classifier Behaviour
In the field of pattern recognition, the concept of Multiple Classifier Systems (MCSs) was proposed as a method for the development of high performance classification systems. At p...
Giorgio Giacinto, Fabio Roli, Giorgio Fumera