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» A Fast Randomisation Test for Rule Significance
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RSCTC
2010
Springer
155views Fuzzy Logic» more  RSCTC 2010»
13 years 2 months ago
A Fast Randomisation Test for Rule Significance
Randomisation is a method to test the statistical significance of a symbolic rule; it is, however, very expensive. In this paper we present a sequential randomisation test which d...
Ivo Düntsch, Günther Gediga
APPINF
2003
13 years 6 months ago
Fast Frequent Itemset Mining using Compressed Data Representation
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
Raj P. Gopalan, Yudho Giri Sucahyo
WAW
2010
Springer
270views Algorithms» more  WAW 2010»
13 years 2 months ago
Fast Katz and Commuters: Efficient Estimation of Social Relatedness in Large Networks
Abstract. Motivated by social network data mining problems such as link prediction and collaborative filtering, significant research effort has been devoted to computing topologica...
Pooya Esfandiar, Francesco Bonchi, David F. Gleich...
BMCBI
2006
144views more  BMCBI 2006»
13 years 4 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-...
ICPR
2004
IEEE
14 years 5 months ago
Sequence Recognition with Scanning N-Tuple Ensembles
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Applications include both on-line and off-line hand-written character recognition. S...
Simon M. Lucas, Tzu-Kuo Huang