An Adaptive Parameter-Free Optimal Number of Market Segments Estimation Algorithm Based on a New Internal Validity Index
نویسندگان
چکیده
An appropriate optimal number of market segments (ONS) estimation is essential for an enterprise to achieve successful segmentation, but at present, there a serious lack attention this issue in segmentation. In our study, independent adaptive ONS method BWCON-NSDK-means++ proposed by integrating new internal validity index (IVI) Between-Within-Connectivity (BWCON) and stable clustering algorithm Natural-SDK-means++ (NSDK-means++) novel way. First, complete the evaluation dimensions existing IVIs, we designed connectivity formula based on neighbor relationship BWCON with other two commonly considered measures compactness separation. Then, considering stability, parameters performance, NSDK-means++to participate integration where natural was used optimize initial cluster centers (ICCs) determination strategy SDK-means++. At last, ensure objectivity estimated ONS, BWCON-based framework that does not require user set any advance integrated NSDK-means++ into forming practical tool BWCON-NSDK-means++. The final experimental results show are significantly more suitable than their respective models determining demonstrably superior BWCON-KMA, BWCONMBK, BWCON-KM++, BWCON-RKM++, BWCON-SDKM++, BWCON-Single linkage, BWCON-Complete BWCON-Average linkage BWCON-Ward terms estimation. Moreover, as segmentation tool, also outperforms respect inter-market differentiation sub-market size.
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ژورنال
عنوان ژورنال: Cmes-computer Modeling in Engineering & Sciences
سال: 2023
ISSN: ['1526-1492', '1526-1506']
DOI: https://doi.org/10.32604/cmes.2023.026113