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» Iterative Improvement of Neural Classifiers
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PRL
2008
81views more  PRL 2008»
15 years 8 days 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 5 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
15 years 1 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
15 years 1 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 5 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...