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» Mining Prediction Rules from Minority Classes
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IDEAL
2004
Springer
14 years 28 days ago
Prediction of Implicit Protein-Protein Interaction by Optimal Associative Feature Mining
Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein–protein interaction is intrinsic to most cellular processes, pr...
Jae-Hong Eom, Jeong Ho Chang, Byoung-Tak Zhang
BMCBI
2006
144views more  BMCBI 2006»
13 years 7 months ago
Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences
Background: The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation...
Shih-Hau Chiu, Chien-Chi Chen, Gwo-Fang Yuan, Thy-...
DMIN
2007
186views Data Mining» more  DMIN 2007»
13 years 9 months ago
Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
- The classifier built from a data set with a highly skewed class distribution generally predicts the more frequently occurring classes much more often than the infrequently occurr...
Gary M. Weiss, Kate McCarthy, Bibi Zabar
IJCNN
2007
IEEE
14 years 1 months ago
An Associative Memory for Association Rule Mining
— Association Rule Mining is a thoroughly studied problem in Data Mining. Its solution has been aimed for by approaches based on different strategies involving, for instance, the...
Vicente O. Baez-Monroy, Simon O'Keefe
SEMCO
2008
IEEE
14 years 1 months ago
Text Categorization Based on Boosting Association Rules
Associative classification is a novel and powerful method originating from association rule mining. In the previous studies, a relatively small number of high-quality association...
Yongwook Yoon, Gary Geunbae Lee