A Distributed Decision Generation Algorithm based on Granular Computing Using Spark

碩士 === 國立中央大學 === 資訊工程學系 === 105 === The DGAGC algorithm, developed by National Central University, is a classification algorithm based on association-rule mining and searching. The DGAGC algorithm also specifies a distributed computing approach for model training, which is implemented on top of Had...

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Main Authors: Zi-Yan Lin, 林子晏
Other Authors: Wei-Jen Wang
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/8tkurr
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spelling ndltd-TW-105NCU053920942019-05-15T23:39:52Z http://ndltd.ncl.edu.tw/handle/8tkurr A Distributed Decision Generation Algorithm based on Granular Computing Using Spark 植基於Spark系統之分散式粒化運算決策產生演算法 Zi-Yan Lin 林子晏 碩士 國立中央大學 資訊工程學系 105 The DGAGC algorithm, developed by National Central University, is a classification algorithm based on association-rule mining and searching. The DGAGC algorithm also specifies a distributed computing approach for model training, which is implemented on top of Hadoop MapReduce. In this study, we propose a new distributed computing approach for the DGAGC algorithm based on Apache Spark. With the support of in-memory computing by Spark, the new distributed DGAGC algorithm can achieve less average execution time for model training, given four different training data sets. In addition, we also propose a distributed version of the DGAGC for data classification. Wei-Jen Wang 王尉任 2016 學位論文 ; thesis 53 zh-TW
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description 碩士 === 國立中央大學 === 資訊工程學系 === 105 === The DGAGC algorithm, developed by National Central University, is a classification algorithm based on association-rule mining and searching. The DGAGC algorithm also specifies a distributed computing approach for model training, which is implemented on top of Hadoop MapReduce. In this study, we propose a new distributed computing approach for the DGAGC algorithm based on Apache Spark. With the support of in-memory computing by Spark, the new distributed DGAGC algorithm can achieve less average execution time for model training, given four different training data sets. In addition, we also propose a distributed version of the DGAGC for data classification.
author2 Wei-Jen Wang
author_facet Wei-Jen Wang
Zi-Yan Lin
林子晏
author Zi-Yan Lin
林子晏
spellingShingle Zi-Yan Lin
林子晏
A Distributed Decision Generation Algorithm based on Granular Computing Using Spark
author_sort Zi-Yan Lin
title A Distributed Decision Generation Algorithm based on Granular Computing Using Spark
title_short A Distributed Decision Generation Algorithm based on Granular Computing Using Spark
title_full A Distributed Decision Generation Algorithm based on Granular Computing Using Spark
title_fullStr A Distributed Decision Generation Algorithm based on Granular Computing Using Spark
title_full_unstemmed A Distributed Decision Generation Algorithm based on Granular Computing Using Spark
title_sort distributed decision generation algorithm based on granular computing using spark
publishDate 2016
url http://ndltd.ncl.edu.tw/handle/8tkurr
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