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Title: Performance analysis of a rule based Mining framework in predicting Retail sales
Researcher: Bhanu D
Guide(s): Pavai madheswari S
Keywords: Coalescent Dataset
Data Mining
Group based Mining of Association Rules
Upload Date: 12-Nov-2014
University: Anna University
Completed Date: 01/03/2010
Abstract: newlineData Mining is the process of extracting interesting and previously newlineunknown patterns and correlations from data stored in huge data repositories newlineAssociation Rule Mining a descriptive mining technique of Data Mining is newlinethe process of discovering items which tend to occur together in transactions newlineAssociation rules are interesting correlations among attributes in a database newlineA key issue that needs more concern when using Association Rule newlineMining is the soundness of the rules external to the dataset from which they newlineare generated Rules are usually the derivative of the patterns in a specific newlinedata set When a different phenomenon occurs the changes in the set of rules newlineobtained from the new setting could be significant This thesis provides a newlineGroup based Mining of Association Rules G MAR model by paying special newlineattention as how the variation between two different settings affects the newlinechanges of the rules based on the notion of fine partitioned groups termed as newlinefactions Using this G MAR model a simple technique called Coalescent newlineDataset is proposed to get a fine approximation of the set of rules for a new newlinesituation newline
Pagination: xvii, 140p.
Appears in Departments:Faculty of Science and Humanities

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04_acknowledgement.pdf6.96 kBAdobe PDFView/Open
05_content.pdf30.85 kBAdobe PDFView/Open
06_chapter1.pdf66.6 kBAdobe PDFView/Open
07_chapter2.pdf61.58 kBAdobe PDFView/Open
08_chapter3.pdf552.63 kBAdobe PDFView/Open
09_chapter4.pdf347.07 kBAdobe PDFView/Open
10_chapter5.pdf914.87 kBAdobe PDFView/Open
11_chapter6.pdf25.06 kBAdobe PDFView/Open
12_reference.pdf58.89 kBAdobe PDFView/Open
13_publication.pdf8.84 kBAdobe PDFView/Open
14_vitae.pdf6.07 kBAdobe PDFView/Open

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