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Research on Efficient K_Means Parallel Algorithm Based on Hadoop Distributed Architecture
| Content Provider | Scilit |
|---|---|
| Author | Qian, Lin Wang, Lin Mei, Zhu Yu, Jun Zhu, Guangxin Song, Debing Xu, Mingjie |
| Copyright Year | 2018 |
| Description | Journal: Iop Conference Series: Materials Science and Engineering Focusing on the problems of K-means algorithm that has high time complexity, slow convergence, lower clustering accuracy, slow operating speed, an efficient K-means parallel algorithm based on Hadoop system and MapReduce framework is proposed. Firstly, the algorithm uses K selective sorting algorithm to improve the sampling efficiency; Secondly, the iterative center is updated by using the weight replacement policy; finally, the initial center point is obtained based on the sample pretreatment strategy. Experimental results show that the proposed algorithm not only has good convergence, accuracy and speedup, but also can improve performance of the algorithm. |
| Related Links | http://iopscience.iop.org/article/10.1088/1757-899X/452/4/042066/pdf |
| ISSN | 17578981 |
| e-ISSN | 1757899X |
| DOI | 10.1088/1757-899x/452/4/042066 |
| Journal | Iop Conference Series: Materials Science and Engineering |
| Issue Number | 4 |
| Volume Number | 452 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2018-12-13 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Materials Science and Engineering Hardware and Architecture K Means Parallel Algorithm Algorithm Based |
| Content Type | Text |
| Resource Type | Article |
