کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
483374 | 1446231 | 2006 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A tandem clustering process for multimodal datasets A tandem clustering process for multimodal datasets](/preview/png/483374.png)
Clustering multimodal datasets can be problematic when a conventional algorithm such as k-means is applied due to its implicit assumption of Gaussian distribution of the dataset. This paper proposes a tandem clustering process for multimodal data sets. The proposed method first divides the multimodal dataset into many small pre-clusters by applying k-means or fuzzy k-means algorithm. These pre-clusters are then clustered again by agglomerative hierarchical clustering method using Kullback–Leibler divergence as an initial measure of dissimilarity. Benchmark results show that the proposed approach is not only effective at extracting the multimodal clusters but also efficient in computational time and relatively robust at the presence of outliers.
Journal: European Journal of Operational Research - Volume 168, Issue 3, 1 February 2006, Pages 998–1008