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» Highly Scalable Rough Set Reducts Generation
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KAIS
2000
86views more  KAIS 2000»
13 years 9 months ago
A Mathematical Foundation for Improved Reduct Generation in Information Systems
When data sets are analyzed, statistical pattern recognition is often used to find the information hidden in the data. Another approach to information discovery is data mining. Dat...
Janusz A. Starzyk, Dale E. Nelson, Kirk Sturtz
ESWA
2007
105views more  ESWA 2007»
13 years 9 months ago
Applying rough sets to prevent customer complaints for IC packaging foundry
Packaging is classified as one of back-end processes in the integrated circuits (ICs) manufacturing, highly capital-intensive and involves complex processes. Unlike the front-end...
Hsu-Hao Yang, Tzu-Chiang Liu, Yen-Ting Lin
PR
2007
129views more  PR 2007»
13 years 9 months ago
EROS: Ensemble rough subspaces
Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...
Qinghua Hu, Daren Yu, Zongxia Xie, Xiaodong Li
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 10 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
ET
1998
52views more  ET 1998»
13 years 9 months ago
Scalable Test Generators for High-Speed Datapath Circuits
This paper explores the design of efficient test sets and test-pattern generators for online BIST. The target applications are high-performance, scalable datapath circuits for whi...
Hussain Al-Asaad, John P. Hayes, Brian T. Murray