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Study on cluster analysis characteristics and classification capabilities 2014 a case study of satisfaction regarding hotels and bed amp breakfasts of Chinese tourists in Taiwan


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Abstract

Cluster analysis is a multivariate statistical analysis method for the classification of samples based on the principle of 201Clike attracts like201D. It requires reasonable classification according to the characteristics in a reasonable manner, and without any mode for reference, in other words, classification is implemented without any prior knowledge. It has been applied in many aspects. In this paper, four cluster analysis methods are used to study the questionnaire data of Chinese tourists2019 satisfaction regarding Taiwan2019s hotels and Bed amp Breakfasts, (BampBs). First, this study applied principal component analysis in reducing questionnaire variables, and then gray relational analysis to assess the overall satisfaction performance. By sorting the overall satisfaction performance values, the performance values combined with the principle components were used as the testing sample data. Afterwards, the samples were categorized into three categories and four categories according to performance value. The four cluster analysis methods were used for clustering the principle components in order to observe their cluster performance and classification capabilities. The testing data testing results suggested that GK Cluster can obtain good cluster performance and good classification capabilities.


Keywords


Pages

Total Pages: 6
Pages: 103-108

DOI
10.1080/10798587.2016.1139285


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Published

Volume: 23
Issue: 1
Year: 2016

Cite this document


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JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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