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Techniques for detection of multi-dimensional clusters in arbitrary subspaces of high-dimensional data
Techniques for detection of multi-dimensional clusters in arbitrary subspaces of high-dimensional data
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机译:高维数据任意子空间中多维簇的检测技术
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摘要
Clustering techniques for data analysis are provided. In one aspect, a method for finding clusters in a database containing a plurality of input attributes associated with a plurality of samples is provided. The method comprises the following steps. One-dimensional clusters are detected for each of one or more of the input attributes in the database. The one-dimensional clusters are used to determine one or more subspaces wherein at least one multi-dimensional cluster of the samples can exist. One or more multivariate clusters are detected in the one or more subspaces. Each input attribute, e.g., a gene, may comprise one or more values corresponding to one or more of the samples, e.g., medical patients, in the database.
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