A Novel Clustering Algorithm Based on Self-Organization Procedure
碩士 === 國立新竹教育大學 === 人資處數學教育碩士班 === 99 === Abstract This study presents a method to select the parameter in Chen and Shiu's (2007) clustering algorithm. The data points in the proposed clustering algorithm can self-organize local optimal cluster number without using cluster validity function...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/35045936095034037223 |
| Summary: | 碩士 === 國立新竹教育大學 === 人資處數學教育碩士班 === 99 === Abstract
This study presents a method to select the parameter in Chen and Shiu's (2007) clustering algorithm. The data points in the proposed clustering algorithm can self-organize local optimal cluster number without using cluster validity functions. The proposed clustering method is also robust to outliers based on the numerical experiments. Therefore, the proposed algorithms exhibits two robust clustering characteristics: (i) robust to the initialization (cluster number and initial guesses), (ii) robust to noise and outliers. Several numerical data and actual data sets are used in the proposed algorithm to show these good aspects.
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