Self-Updating Process with B-splines on Functional Data Clustering
碩士 === 國立臺北大學 === 統計學系 === 106 === The self-updating process (SUP) is competitive in clustering data with noise, data with a large number of clusters, and unbalanced data. This paper presents an extension of SUP to functional data clustering by the use of B-spline basis functions. The curves in data...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/23uyn2 |