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High-dimensional data mining: subspace clustering, outlier detection and applications to classification
DownloadSpring 2010
Data mining in high dimensionality almost inevitably faces the consequences of increasing sparsity and declining differentiation between points. This is problematic because we usually exploit these differences for approaches such as clustering and outlier detection. In addition, the exponentially...
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