Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/26421
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dc.coverage.spatialCertain investigations on eager and Lazy learning associative classificationen_US
dc.date.accessioned2014-10-09T09:12:25Z-
dc.date.available2014-10-09T09:12:25Z-
dc.date.issued2014-10-09-
dc.identifier.urihttp://hdl.handle.net/10603/26421-
dc.description.abstractnewlineCombining different problem solving methods is a very active research area newlinein data mining Associative classification is a recent and rewarding technique in newlinedata mining that applies the methodology of association rule mining into newlineclassification and achieves higher classification accuracy It is a known fact that newlineassociative classification typically yields a large number of rules If all the newlinegenerated class association rules are used in the classifier then accuracy of the newlineclassifier may be high but the classification process will be slow and timeconsuming newlineHence generating high quality class association rules and constructing newlinethe accurate classifier are indeed a challenging task newlineen_US
dc.format.extentxix, 150p.en_US
dc.languageEnglishen_US
dc.relationp141-147.en_US
dc.rightsuniversityen_US
dc.titleCertain investigations on eager and Lazy learning associative classificationen_US
dc.title.alternativeen_US
dc.creator.researcherSyed ibrahim S Pen_US
dc.subject.keywordAssociative classificationen_US
dc.description.notereference p141-147.en_US
dc.contributor.guideChandran K Ren_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Information and Communication Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01-02-2013en_US
dc.date.awarded30-02-2013en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificate.pdf83.3 kBAdobe PDFView/Open
03_abstract.pdf15.33 kBAdobe PDFView/Open
04_acknowledgement.pdf19.96 kBAdobe PDFView/Open
05_content.pdf77.81 kBAdobe PDFView/Open
06_chapter1.pdf85.99 kBAdobe PDFView/Open
07_chapter2.pdf245.12 kBAdobe PDFView/Open
08_chapter3.pdf145.37 kBAdobe PDFView/Open
09_chapter4.pdf133.63 kBAdobe PDFView/Open
10_chapter5.pdf126.57 kBAdobe PDFView/Open
11_chapter6.pdf110.47 kBAdobe PDFView/Open
12_chapter7.pdf1.88 MBAdobe PDFView/Open
13_reference.pdf204.77 kBAdobe PDFView/Open
14_publication.pdf71.39 kBAdobe PDFView/Open
15_vitae.pdf19.92 kBAdobe PDFView/Open


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