A Reformed K-Nearest Neighbors Algorithm for Big Data Sets
| dc.contributor.author | Vo, Ngoc Phu | |
| dc.contributor.author | Vo, Thị Ngoc Tran | |
| dc.date.accessioned | 2024-08-21T02:50:15Z | |
| dc.date.available | 2024-08-21T02:50:15Z | |
| dc.date.issued | 2018-03-08 | |
| dc.description | 13 tr. | |
| dc.description.abstract | In This Research, We Propose An Improvement To K-NN To Process Big Datasets In A Shortened Execution Time. The Reformed K-Nearest Neighbors Algorithm (R-K-NN) Can Be Implemented On Large Datasets With Millions Or Even Billions Of Data Records. R-K-NN Is Tested On A Data Set With 500,000 Records. The Execution Time Of R-K-NN Is Much Shorter Than That Of K-NN. In Addition, R-K-NN Is Implemented In A Parallel Network System With Hadoop Map (M) And Hadoop Reduce (R). | |
| dc.identifier.uri | https://oerrepository.ntt.edu.vn/handle/298300331/40 | |
| dc.language.iso | vi_VN | |
| dc.publisher | Trường Đại học Nguyễn Tất Thành (Tạp chí Khoa học công nghệ NTT) | |
| dc.subject | K-Nearest Neighbors Algorithm | |
| dc.subject | Parallel Network Environment | |
| dc.subject | Distributed System | |
| dc.title | A Reformed K-Nearest Neighbors Algorithm for Big Data Sets | |
| dc.type | Article |