A Distributed System for Pattern Recognition and Machine Learning

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Added by benbanbun on 2010-11-15 12:16

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Creator(s): Alexander Arimond

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This thesis deals with the development and evaluation of a system which integrates distributed computing frameworks into RapidMiner. A special focus is put on
utilizing MapReduce as a programming model. The software frameworks Hadoop, GridGain and Oracle Coherence are reviewed and evaluated with respect to their suitablility to fit into the context of RapidMiner. The developed system provides effective means for transparently utilizing these frameworks and enabling RapidMiner processes to parallelize their computations within a distributed environment.

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A Distributed System for Pattern Recognition and Machine Learning This thesis deals with the development and evaluation of a system which integrates distributed computing frameworks into RapidMiner. A special focus is put on utilizing MapReduce as a programming model. The software frameworks Hadoop, GridGain and Oracle Coherence are reviewed and evaluated with respect to their suitablility to fit into the context of RapidMiner. The developed system provides effective means for transparently utilizing these frameworks and enabling RapidMiner processes to parallelize their computations within a distributed environment. Alexander Arimond