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» On learning algorithm selection for classification
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BIBM
2009
IEEE
192views Bioinformatics» more  BIBM 2009»
14 years 2 months ago
A Multi-task Feature Selection Filter for Microarray Classification
A major challenge in microarray classification and biomarker discovery is dealing with small-sample high-dimensional data where the number of genes used as features is typically o...
Liang Lan, Slobodan Vucetic
JUCS
2008
130views more  JUCS 2008»
13 years 7 months ago
Feature Selection for the Classification of Large Document Collections
: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of...
Janez Brank, Dunja Mladenic, Marko Grobelnik, Nata...
TFS
2008
230views more  TFS 2008»
13 years 7 months ago
SGERD: A Steady-State Genetic Algorithm for Extracting Fuzzy Classification Rules From Data
Abstract--This paper considers the automatic design of fuzzyrule-based classification systems from labeled data. The performance of classifiers and the interpretability of generate...
Eghbal G. Mansoori, Mansoor J. Zolghadri, Seraj D....
FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
14 years 1 months ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo
CP
2010
Springer
13 years 5 months ago
Ensemble Classification for Constraint Solver Configuration
The automatic tuning of the parameters of algorithms and automatic selection of algorithms has received a lot of attention recently. One possible approach is the use of machine lea...
Lars Kotthoff, Ian Miguel, Peter Nightingale