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In the recent years the scope of data mining has evolved into an active area of research because of the previously unknown and interesting knowledge from very large database collection. The data mining is applied on a variety of applications in multiple domains like in business, IT and many more sectors. In Data Mining the major problem which receives great attention by the community is the classification of the data. The classification of data should be such that it could be they can be easily verified and should be easily interpreted by the humans. In this paper we would be studying various data mining techniques so that we can find few combinations for enhancing the hybrid technique which would be having multiple techniques involved so enhance the usability of the application. We would be studying CHARM Algorithm, CM-SPAM Algorithm, Apriori Algorithm, MOPNAR Algorithm and the Top K Rules.
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Study on Positive and Negative Rule Based Mining Techniques for E-Commerce Applications
2016, Association of Scientists, Developers and Faculties
in English
8192986659 9788192986654
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Feedback?June 20, 2016 | Created by ASDF Administrator | Added new book. |