Clustering quality metrics for subspace clustering
نویسندگان
چکیده
منابع مشابه
Clustering Consistent Sparse Subspace Clustering
Subspace clustering is the problem of clustering data points into a union of lowdimensional linear/affine subspaces. It is the mathematical abstraction of many important problems in computer vision, image processing and machine learning. A line of recent work [4, 19, 24, 20] provided strong theoretical guarantee for sparse subspace clustering [4], the state-of-the-art algorithm for subspace clu...
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Subspace clustering is recognized as a more general and difficult task than standard clustering since it requires to identify not only objects sharing similar feature values but also the various subspaces where these similarities appear. Many approaches have been investigated for subspace clustering in the literature using various clustering paradigms. The reader is referred for instance to [5]...
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Clustering is an established data mining technique for grouping objects based on their mutual similarity. Since in today’s applications, however, usually many characteristics for each object are recorded, one cannot expect to find similar objects by considering all attributes together. In contrast, valuable clusters are hidden in subspace projections of the data. As a general solution to this p...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2020
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2020.107328