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» Mining Positive and Negative Fuzzy Association Rules
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RSKT
2009
Springer
15 years 4 months ago
Three-Way Decision: An Interpretation of Rules in Rough Set Theory
Abstract. A new interpretation of rules in rough set theory is introduced. According to the positive, boundary, and negative regions of a set, one can make a three-way decision: ac...
Yiyu Yao
BMCBI
2007
147views more  BMCBI 2007»
14 years 9 months ago
Predicting combinatorial binding of transcription factors to regulatory elements in the human genome by association rule mining
Background: Cis-acting transcriptional regulatory elements in mammalian genomes typically contain specific combinations of binding sites for various transcription factors. Althoug...
Xochitl C. Morgan, Shulin Ni, Daniel P. Miranker, ...
ICPR
2008
IEEE
15 years 4 months ago
A fuzzy c-means algorithm using a correlation metrics and gene ontology
A fuzzy c-means algorithm was adapted for analyzing microarray data. The adaptation consisted of initialization of fuzzy centroids using gene ontology information and the use of P...
Mingrui Zhang, Terry M. Therneau, Michael A. McKen...
JMLR
2008
117views more  JMLR 2008»
14 years 9 months ago
Closed Sets for Labeled Data
Closed sets have been proven successful in the context of compacted data representation for association rule learning. However, their use is mainly descriptive, dealing only with ...
Gemma C. Garriga, Petra Kralj, Nada Lavrac
BMCBI
2007
166views more  BMCBI 2007»
14 years 9 months ago
PathFinder: mining signal transduction pathway segments from protein-protein interaction networks
Background: A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of ...
Gürkan Bebek, Jiong Yang