Computational cognition for big data analytics
The machine learning algorithms like Projection Based Learning algorithm in Meta-cognitive Radial Basis Function Network (PBL-McRBFN) look up to human brain in attempts to make its computation more efficient. However, the performance of this algorithm is limited by the nature of sequential learning....
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2016
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| Online Access: | http://hdl.handle.net/10356/69171 |
| _version_ | 1811692258893758464 |
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| author | Yuan, Yiyang |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Yuan, Yiyang |
| author_sort | Yuan, Yiyang |
| collection | NTU |
| description | The machine learning algorithms like Projection Based Learning algorithm in Meta-cognitive Radial Basis Function Network (PBL-McRBFN) look up to human brain in attempts to make its computation more efficient. However, the performance of this algorithm is limited by the nature of sequential learning. In this project we bring Big Data-era technology Apache Spark cluster computing platform to use with this algorithm in an attempt to achieve collaborative distributed learning. Amidst the various difficulties, the project achieved a partial success while discovering other potential issues in using Spark to achieve the goal. |
| first_indexed | 2024-10-01T06:32:56Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/69171 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:32:56Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/691712023-03-03T20:47:00Z Computational cognition for big data analytics Yuan, Yiyang School of Computer Engineering Suresh Sundaram DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence The machine learning algorithms like Projection Based Learning algorithm in Meta-cognitive Radial Basis Function Network (PBL-McRBFN) look up to human brain in attempts to make its computation more efficient. However, the performance of this algorithm is limited by the nature of sequential learning. In this project we bring Big Data-era technology Apache Spark cluster computing platform to use with this algorithm in an attempt to achieve collaborative distributed learning. Amidst the various difficulties, the project achieved a partial success while discovering other potential issues in using Spark to achieve the goal. Bachelor of Engineering (Computer Science) 2016-11-14T03:29:10Z 2016-11-14T03:29:10Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/69171 en Nanyang Technological University 50 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Yuan, Yiyang Computational cognition for big data analytics |
| title | Computational cognition for big data analytics |
| title_full | Computational cognition for big data analytics |
| title_fullStr | Computational cognition for big data analytics |
| title_full_unstemmed | Computational cognition for big data analytics |
| title_short | Computational cognition for big data analytics |
| title_sort | computational cognition for big data analytics |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | http://hdl.handle.net/10356/69171 |
| work_keys_str_mv | AT yuanyiyang computationalcognitionforbigdataanalytics |