ClustNails: Visual analysis of subspace clusters
نویسندگان
چکیده
منابع مشابه
ClustNails: Visual Analysis of Subspace Clusters
Subspace clustering addresses an important problem in clustering multi-dimensional data. In sparse multi-dimensional data, many dimensions are irrelevant and obscure the cluster boundaries. Subspace clustering helps by mining the clusters present in only locally relevant subsets of dimensions. However, understanding the result of subspace clustering by analysts is not trivial. In addition to th...
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Many clustering algorithms are not applicable to high-dimensional feature spaces, because the clusters often exist only in specific subspaces of the original feature space. Those clusters are also called subspace clusters. In this paper, we propose the algorithm HiSC (Hierarchical Subspace Clustering) that can detect hierarchies of nested subspace clusters, i.e. the relationships of lowerdimens...
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Traditional similarity measurements often become meaningless when dimensions of datasets increase. Subspace clustering has been proposed to find clusters embedded in subspaces of high dimensional datasets. Many existing algorithms use a grid based approach to partition the data space into nonoverlapping rectangle cells, and then identify connected dense cells as clusters. The rigid boundaries o...
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Extraction of knowledge from data and using it for decision making is vital in various real-world problems, particularly in the financial domain. We identify several financial problems, which require the mining of actionable subspaces defined by objects and attributes over a sequence of time. These subspaces are actionable in the sense that they have the ability to suggest profitable action for...
متن کاملVisual Quality Assessment of Subspace Clusterings
The quality assessment of results of clustering algorithms is challenging as different cluster methodologies lead to different cluster characteristics and topologies. A further complication is that in high-dimensional data, subspace clustering adds to the complexity by detecting clusters in multiple different lower-dimensional projections. The quality assessment for (subspace) clustering is esp...
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ژورنال
عنوان ژورنال: Tsinghua Science and Technology
سال: 2012
ISSN: 1007-0214
DOI: 10.1109/tst.2012.6297588