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» Phenomenal Data Mining: From Data to Phenomena
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JMLR
2010
134views more  JMLR 2010»
13 years 2 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
CIKM
2006
Springer
13 years 11 months ago
Mining coherent patterns from heterogeneous microarray data
Microarray technology is a powerful tool for geneticists to monitor interactions among tens of thousands of genes simultaneously. There has been extensive research on coherent sub...
Xiang Zhang, Wei Wang 0010
SIGSOFT
2010
ACM
13 years 5 months ago
LINKSTER: enabling efficient manual inspection and annotation of mined data
While many uses of mined software engineering data are automatic in nature, some techniques and studies either require, or can be improved, by manual methods. Unfortunately, manua...
Christian Bird, Adrian Bachmann, Foyzur Rahman, Ab...
ESWA
2008
128views more  ESWA 2008»
13 years 7 months ago
Mining the data from a hyperheuristic approach using associative classification
Associative classification is a promising classification approach that utilises association rule mining to construct accurate classification models. In this paper, we investigate ...
Fadi A. Thabtah, Peter I. Cowling
GEOINFORMATICA
2006
102views more  GEOINFORMATICA 2006»
13 years 7 months ago
Mining Co-Location Patterns with Rare Events from Spatial Data Sets
Abstract A co-location pattern is a group of spatial features/events that are frequently co-located in the same region. For example, human cases of West Nile Virus often occur in r...
Yan Huang, Jian Pei, Hui Xiong