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» Rough Set Approach to CBR
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DAWAK
2006
Springer
13 years 11 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...
AEPIA
2002
159views more  AEPIA 2002»
13 years 7 months ago
Analysing Rough Sets weighting methods for Case-Based Reasoning Systems
Case-Based Reasoning systems retrieve cases using a similarity function based on the K-NN or some derivatives. These functions are sensitive to irrelevant, interacting or noisy fe...
Maria Salamó, Elisabet Golobardes
FUZZIEEE
2007
IEEE
14 years 1 months ago
Distance Measure Assisted Rough Set Feature Selection
Abstract— Feature Selection (FS) is a technique for dimensionality reduction. Its aims are to select a subset of the original features of a dataset which are rich in the most use...
Neil MacParthalain, Qiang Shen, Richard Jensen
RSKT
2010
Springer
13 years 6 months ago
Ordered Weighted Average Based Fuzzy Rough Sets
Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied t...
Chris Cornelis, Nele Verbiest, Richard Jensen
FUIN
2006
160views more  FUIN 2006»
13 years 7 months ago
Behavioral Pattern Identification Through Rough Set Modeling
This paper introduces an approach to behavioral pattern identification as a part of a study of temporal patterns in complex dynamical systems. Rough set theory introduced by Zdzisl...
Jan G. Bazan