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ENGL
2007
191views more  ENGL 2007»
15 years 6 months ago
Data Mining for extraction of fuzzy IF-THEN rules using Mamdani and Takagi-Sugeno-Kang FIS
— This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automati...
Juan E. Moreno, Oscar Castillo, Juan R. Castro, Lu...
AUSAI
2005
Springer
16 years 7 days ago
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
Geoffrey I. Webb
PVLDB
2008
82views more  PVLDB 2008»
15 years 6 months ago
Mining non-redundant high order correlations in binary data
Many approaches have been proposed to find correlations in binary data. Usually, these methods focus on pair-wise correlations. In biology applications, it is important to find co...
Xiang Zhang, Feng Pan, Wei Wang 0010, Andrew B. No...
BIBM
2007
IEEE
171views Bioinformatics» more  BIBM 2007»
16 years 1 months ago
GenMiner: Mining Informative Association Rules from Genomic Data
GENMINER is a smart adaptation of closed itemsets based association rules extraction to genomic data. It takes advantage of the novel NORDI discretization method and of the CLOSE ...
Ricardo Martínez, Claude Pasquier, Nicolas ...
DAWAK
2006
Springer
15 years 10 months ago
Mining Direct Marketing Data by Ensembles of Weak Learners and Rough Set Methods
This paper describes problem of prediction that is based on direct marketing data coming from Nationwide Products and Services Questionnaire (NPSQ) prepared by Polish division of A...
Jerzy Blaszczynski, Krzysztof Dembczynski, Wojciec...