Fuzzy clustering algorithm for outlier-interval data based on the robust exponent distance
| العنوان: | Fuzzy clustering algorithm for outlier-interval data based on the robust exponent distance |
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| المؤلفون: | Dinh Phamtoan, Khanh Nguyenhuu, Tai Vovan |
| المصدر: | Applied Intelligence. 52:6276-6291 |
| بيانات النشر: | Springer Science and Business Media LLC, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Fuzzy clustering, Computer science, Image (mathematics), ComputingMethodologies_PATTERNRECOGNITION, Artificial Intelligence, Robustness (computer science), Face (geometry), Outlier, Exponent, Cluster analysis, MATLAB, Algorithm, computer, computer.programming_language |
| الوصف: | The outlier elements of a data are ones that differs significantly from others. For many reasons, we have to face with outlier elements in data analysis for the different fields. Because an outlier element can cause the serious problems in statistical analyses, studying about it is interested in many researchers. This article proposes the fuzzy clustering algorithm for outlier - interval data based on the robust exponent distance to overcome the drawback of traditional clustering algorithm which to clean the outliers before performing. The outstanding advantage of this algorithm is to find the suitable number of clusters, to cluster for the interval data with outlier elements, and to determine the probability belonging to clusters for the intervals at the same time. The proposed algorithm is described step by step via numerical examples, and can be performed effectively by the Matlab procedure. In addition, it also applied in reality with the air pollution, mushroom, and image data sets. These real applications demonstrate the robustness of the proposed algorithm in comparison with the existing ones. |
| تدمد: | 1573-7497 0924-669X |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_________::111b46e8081479d4d4a684329ecbd56eTest https://doi.org/10.1007/s10489-021-02773-wTest |
| حقوق: | CLOSED |
| رقم الانضمام: | edsair.doi...........111b46e8081479d4d4a684329ecbd56e |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15737497 0924669X |
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