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» Predicting mining activity with parallel genetic algorithms
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ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
14 years 1 months ago
A Scalable Collaborative Filtering Framework Based on Co-Clustering
Collaborative filtering-based recommender systems, which automatically predict preferred products of a user using known preferences of other users, have become extremely popular ...
Thomas George, Srujana Merugu
PKDD
2005
Springer
161views Data Mining» more  PKDD 2005»
14 years 1 months ago
Active Sampling for Knowledge Discovery from Biomedical Data
Abstract. We describe work aimed at cost-constrained knowledge discovery in the biomedical domain. To improve the diagnostic/prognostic models of cancer, new biomarkers are studied...
Sriharsha Veeramachaneni, Francesca Demichelis, Em...
ICDM
2009
IEEE
199views Data Mining» more  ICDM 2009»
14 years 2 months ago
Active Learning with Adaptive Heterogeneous Ensembles
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Zhenyu Lu, Xindong Wu, Josh Bongard
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 9 months ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard
ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 7 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...