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» Evaluation of Sampling for Data Mining of Association Rules
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TSMC
2002
135views more  TSMC 2002»
15 years 5 months ago
Fuzzy decision tree, linguistic rules and fuzzy knowledge-based network: generation and evaluation
A fuzzy knowledge-based network is developed based on the linguistic rules extracted from a fuzzy decision tree. A scheme for automatic linguistic discretization of continuous attr...
Sushmita Mitra, Kishori M. Konwar, Sankar K. Pal
BMCBI
2008
226views more  BMCBI 2008»
15 years 6 months ago
ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining
Background: New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellu...
Tianxiao Huan, Andrey Y. Sivachenko, Scott H. Harr...
144
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CORR
2010
Springer
108views Education» more  CORR 2010»
15 years 6 months ago
Mining The Successful Binary Combinations: Methodology and A Simple Case Study
The importance of finding the characteristics leading to either a success or a failure is one of the driving forces of data mining. The various application areas of finding succes...
Yuval Cohen
159
Voted
PKDD
2005
Springer
110views Data Mining» more  PKDD 2005»
15 years 11 months ago
k-Anonymous Patterns
It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in orde...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
GECCO
2003
Springer
15 years 11 months ago
Mining Comprehensible Clustering Rules with an Evolutionary Algorithm
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...