Performance Analysis of Association Rule Mining Algorithms - Singh, Sandeep Pratap
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Association rule mining techniques are important part of data mining to derive relationship between attributes of large databases. Association related rule mining have evolved huge interest among researchers as many challenging problems can be solved using them. Numerous algorithms have been discovered for deriving association rules effectively. It has been evaluated that not all algorithms can give similar results in all scenarios, so decoding these merits becomes important. In thisassociation rule mining algorithms were analyzed ,Comparison of these algorithms were experimentally performed based on different datasets and different parameters.…mehr

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Produktbeschreibung
Association rule mining techniques are important part of data mining to derive relationship between attributes of large databases. Association related rule mining have evolved huge interest among researchers as many challenging problems can be solved using them. Numerous algorithms have been discovered for deriving association rules effectively. It has been evaluated that not all algorithms can give similar results in all scenarios, so decoding these merits becomes important. In thisassociation rule mining algorithms were analyzed ,Comparison of these algorithms were experimentally performed based on different datasets and different parameters.
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Autorenporträt
Sandeep Pratap Singh received his B.E. and M.Tech degrees in CSE. Presently, working as an Assistant Professor (SG) at the School of Computer Science, UPES, Dehradun, India. His research interest lies in data mining, fraud detection, and biomedical image processing published 3 books and many papers in conferences and journals.