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» Attribute reduction in decision-theoretic rough set models
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KBS
2008
98views more  KBS 2008»
14 years 8 months ago
Mixed feature selection based on granulation and approximation
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
Qinghua Hu, Jinfu Liu, Daren Yu
75
Voted
FUIN
2002
108views more  FUIN 2002»
14 years 9 months ago
Approximate Entropy Reducts
We use information entropy measure to extend the rough set based notion of a reduct. We introduce the Approximate Entropy Reduction Principle (AERP). It states that any simplificat...
Dominik Slezak
IBERAMIA
2004
Springer
15 years 2 months ago
Applying Rough Sets Reduction Techniques to the Construction of a Fuzzy Rule Base for Case Based Reasoning
Early work on Case Based Reasoning reported in the literature shows the importance of soft computing techniques applied to different stages of the classical 4-step CBR life cycle. ...
Florentino Fdez-Riverola, Fernando Díaz, Ju...
EMS
2008
IEEE
15 years 3 months ago
Rough Set Generating Prediction Rules for Stock Price Movement
This paper presents rough sets generating prediction rules scheme for stock price movement. The scheme was able to extract knowledge in the form of rules from daily stock movement...
Hameed Al-Qaheri, Shariffah Zamoon, Aboul Ella Has...
JCIT
2007
126views more  JCIT 2007»
14 years 9 months ago
Rough Petri Net Model (RPNM) For knowledge Representation, Rules Generation and Reasoning
Rough Petri nets model (RPNM) for knowledge representation, rule generation, and reasoning is presented in this paper. An algorithm for verifying the consistency of a rough knowle...
Hala S. Own