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» A Rule Format for Associativity
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CSDA
2007
99views more  CSDA 2007»
15 years 4 months ago
CLUES: A non-parametric clustering method based on local shrinking
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
Xiaogang Wang, Weiliang Qiu, Ruben H. Zamar
JSW
2008
99views more  JSW 2008»
15 years 4 months ago
Using Data Mining in MURA Graphic Problems
The MURA phenomenon will result lots of problems in Photomask and TFT-LCD industries as well. In this paper, we designed and developed a MURA related association rules which suitab...
Wen-Hsing Kao, Jason C. Hung, Victoria Hsu
ML
2008
ACM
15 years 4 months ago
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns
Standard pattern discovery techniques, such as association rules, suffer an extreme risk of finding very large numbers of spurious patterns for many knowledge discovery tasks. The...
Geoffrey I. Webb
FMSD
2007
138views more  FMSD 2007»
15 years 4 months ago
Object oriented concepts identification from formal B specifications
This paper addresses the graphical representation of static aspects of B specifications, using UML class diagrams. These diagrams can help understand the specification for stakeho...
Akram Idani, Yves Ledru
MP
2006
84views more  MP 2006»
15 years 4 months ago
On the behavior of the homogeneous self-dual model for conic convex optimization
Abstract. There is a natural norm associated with a starting point of the homogeneous selfdual (HSD) embedding model for conic convex optimization. In this norm two measures of the...
Robert M. Freund