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ICDM
2009
IEEE
124views Data Mining» more  ICDM 2009»
14 years 2 months ago
Rule Ensembles for Multi-target Regression
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...
Timo Aho, Bernard Zenko, Saso Dzeroski
BMCBI
2010
108views more  BMCBI 2010»
13 years 8 months ago
A genetic ensemble approach for gene-gene interaction identification
Background: It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases...
Pengyi Yang, Joshua W. K. Ho, Albert Y. Zomaya, Bi...
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 8 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
14 years 2 months ago
A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation
Surrogate-Assisted Memetic Algorithm(SAMA) is a hybrid evolutionary algorithm, particularly a memetic algorithm that employs surrogate models in the optimization search. Since mos...
Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendh...
CICLING
2010
Springer
13 years 11 months ago
ETL Ensembles for Chunking, NER and SRL
We present a new ensemble method that uses Entropy Guided Transformation Learning (ETL) as the base learner. The proposed approach, ETL Committee, combines the main ideas of Baggin...
Cícero Nogueira dos Santos, Ruy Luiz Milidi...