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179
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ICDM
2005
IEEE
153views Data Mining» more  ICDM 2005»
15 years 9 months ago
Speculative Markov Blanket Discovery for Optimal Feature Selection
In this paper we address the problem of learning the Markov blanket of a quantity from data in an efficient manner. Markov blanket discovery can be used in the feature selection ...
Sandeep Yaramakala, Dimitris Margaritis
142
Voted
SDM
2007
SIAM
108views Data Mining» more  SDM 2007»
15 years 5 months ago
Semi-Supervised Dimensionality Reduction
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
137
Voted
ADVIS
2004
Springer
15 years 9 months ago
Multiple Sets of Rules for Text Categorization
An important issue in text mining is how to make use of multiple pieces knowledge discovered to improve future decisions. In this paper, we propose a new approach to combining mult...
Yaxin Bi, Terry J. Anderson, Sally I. McClean
148
Voted
ML
2010
ACM
210views Machine Learning» more  ML 2010»
15 years 2 months ago
Mining frequent closed rooted trees
Many knowledge representation mechanisms are based on tree-like structures, thus symbolizing the fact that certain pieces of information are related in one sense or another. There ...
José L. Balcázar, Albert Bifet, Anto...
135
Voted
AUSDM
2007
Springer
193views Data Mining» more  AUSDM 2007»
15 years 10 months ago
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Elsa Loekito, James Bailey