An Aprori Algorithm in Distributed Data Mining System

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CSTSDE69JR9

An Aprori Algorithm in Distributed Data Mining System

Dr C.Sunil Kumar
Dr C.Sunil Kumar Srrenidhi Institute of Science & Technology
DOI

Abstract

Many existing data mining (DM) tasks can be proficient effectively only in a distributed condition. The ground of distributed data mining (DDM) has therefore gained growing weightage in the preceding decades. The Apriori algorithm (AA) has appeared as one of the greatest Association Rule mining (ARM) algorithms. Ii also provides the foundation algorithm in majority of parallel algorithms (PAs). The size and elevated dimensionality of datasets characteristically existing as a key to difficulty of AR finding, makes it perfect difficulty for solving on numerous processors in parallel. The main causes are the computer memory and central processing unit pace constraints looked by single workstations. This paper is based on an Optimized Distributed AR mining algorithm for biologically distributed information is used in similar and distributed surroundings so that it decreases communication costs.

An Aprori Algorithm in Distributed Data Mining System

Many existing data mining (DM) tasks can be proficient effectively only in a distributed condition. The ground of distributed data mining (DDM) has therefore gained growing weightage in the preceding decades. The Apriori algorithm (AA) has appeared as one of the greatest Association Rule mining (ARM) algorithms. Ii also provides the foundation algorithm in majority of parallel algorithms (PAs). The size and elevated dimensionality of datasets characteristically existing as a key to difficulty of AR finding, makes it perfect difficulty for solving on numerous processors in parallel. The main causes are the computer memory and central processing unit pace constraints looked by single workstations. This paper is based on an Optimized Distributed AR mining algorithm for biologically distributed information is used in similar and distributed surroundings so that it decreases communication costs.

Dr C.Sunil Kumar
Dr C.Sunil Kumar Srrenidhi Institute of Science & Technology

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Dr C.Sunil Kumar. 2013. “. Global Journal of Computer Science and Technology – C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C12): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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An Aprori Algorithm in Distributed Data Mining System

Dr C.Sunil Kumar
Dr C.Sunil Kumar Srrenidhi Institute of Science & Technology

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