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PRL
2006
121views more  PRL 2006»
13 years 7 months ago
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Data reduction plays an important role in machine learning and pattern recognition with a high-dimensional data. In real-world applications data usually exists with hybrid formats...
Qinghua Hu, Daren Yu, Zongxia Xie
GECCO
2006
Springer
214views Optimization» more  GECCO 2006»
13 years 11 months ago
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
13 years 11 months ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman
RSFDGRC
2005
Springer
126views Data Mining» more  RSFDGRC 2005»
14 years 1 months ago
Rough Sets and Higher Order Vagueness
Abstract. We present a rough set approach to vague concept approximation within the adaptive learning framework. In particular, the role of extensions of approximation spaces in se...
Andrzej Skowron, Roman W. Swiniarski
FUIN
2002
123views more  FUIN 2002»
13 years 7 months ago
Learning Rough Set Classifiers from Gene Expressions and Clinical Data
Biological research is currently undergoing a revolution. With the advent of microarray technology the behavior of thousands of genes can be measured simultaneously. This capabilit...
Herman Midelfart, Henryk Jan Komorowski, Kristin N...