Modified global -means algorithm for minimum sum-of-squares clustering problems
نویسندگان
چکیده
منابع مشابه
Modified global k-means algorithm for minimum sum-of-squares clustering problems
k-means algorithm and its variations are known to be fast clustering algorithms. However, they are sensitive to the choice of starting points and inefficient for solving clustering problems in large data sets. Recently, a new version of the k-means algorithm, the global k-means algorithm has been developed. It is an incremental algorithm that dynamically adds one cluster center at a time and us...
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Here, an algorithm is presented for solving the minimum sum-of-squares clustering problems using their difference of convex representations. The proposed algorithm is based on an incremental approach and applies the well known DC algorithm at each iteration. The proposed algorithm is tested and compared with other clustering algorithms using large real world data sets.
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Clustering is an unsupervised technique dealing with problems of organizing a collection of patterns into clusters based on similarity. Most clustering algorithms are based on hierarchical and partitional approaches. Algorithms based on an hierarchical approach generate a dendrogram representing the nested grouping of patterns and similarity levels at which groupings change [19]. Partitional cl...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2008
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2008.04.004