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» Iterative Improvement of Neural Classifiers
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DICS
2006
14 years 11 months ago
Definition and Correct Refinement of Operation Specifications
Abstract. Modern incremental and iterative software engineering processes advocate to build software systems by first creating a highly simpliabstract model of the system which is ...
Thomas Baar, Slavisa Markovic, Frédé...
APBC
2004
132views Bioinformatics» more  APBC 2004»
14 years 11 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
ML
2002
ACM
123views Machine Learning» more  ML 2002»
14 years 9 months ago
Feature Generation Using General Constructor Functions
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Shaul Markovitch, Dan Rosenstein
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 1 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
ISCAS
2006
IEEE
96views Hardware» more  ISCAS 2006»
15 years 3 months ago
On the initialization of the DNMF algorithm
— A subspace supervised learning algorithm named Discriminant Non-negative Matrix Factorization (DNMF) has been recently proposed for classifying human facial expressions. It dec...
Ioan Buciu, Nikos Nikolaidis, Ioannis Pitas