臺灣博碩士論文加值系統

中文摘要
本文提出一種方法選取陳與須(2007)之聚類分析演算法中的參數。在此演算法中，不須指定分群數目與起始值且資料是經由自我組織出一個理想的分群結果。根據數值模擬結果，本文所提之修正演算法具有兩種穩健性：（一）分群結果不受起始值影響；（二）分群結果不受離群值影響。綜合模擬資料與兩組實際資料顯示：本文所提出的演算法能提供一個好的聚類分析結果。

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.

Contents

1. Introduction………………………………………………...1

2. The proposed clustering algorithm………………………..3

3. Numerical examples………………………………………10

4. Conclusions……………………………………………...…21

5. References………………………………………………….22

References
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