A Distributed Decision Generation Algorithm based on Granular Computing Using Spark
| Autor: | Zi-Yan Lin, 林子晏 |
|---|---|
| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 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. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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