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» Mining Prediction Rules from Minority Classes
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IDEAL
2004
Springer
15 years 5 months 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
151
Voted
BMCBI
2006
144views more  BMCBI 2006»
14 years 11 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»
15 years 1 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
15 years 6 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
15 years 6 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