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» Iterative Improvement of Neural Classifiers
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PRL
2008
81views more  PRL 2008»
14 years 9 months ago
Selecting and constructing features using grammatical evolution
A novel method for feature selection and construction is introduced. The method improves the classification accuracy, utilizing the well-established technique of grammatical evolu...
Dimitris Gavrilis, Ioannis G. Tsoulos, Evangelos D...
ICANN
2005
Springer
15 years 3 months ago
Reducing the Effect of Out-Voting Problem in Ensemble Based Incremental Support Vector Machines
Although Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems, they suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
ACSW
2004
14 years 11 months ago
A Market-based Rule Learning System
In this paper, a `market trading' technique is integrated with the techniques of rule discovery and refinement for data mining. A classifier system-inspired model, the market...
Qingqing Zhou, Martin K. Purvis
ESANN
2006
14 years 11 months ago
Recognition of handwritten digits using sparse codes generated by local feature extraction methods
We investigate when sparse coding of sensory inputs can improve performance in a classification task. For this purpose, we use a standard data set, the MNIST database of handwritte...
Rebecca Steinert, Martin Rehn, Anders Lansner
FASE
2005
Springer
15 years 3 months ago
Improving System Understanding via Interactive, Tailorable, Source Code Analysis
In situations in which developers are not familiar with a system or its documentation is inadequate, the system’s source code becomes the only reliable source of information. Unf...
Vladimir Jakobac, Alexander Egyed, Nenad Medvidovi...