High-dimensional cluster analysis with the Masked EM Algorithm

11 Sep 2013Shabnam N. KadirDan F. M. GoodmanKenneth D. Harris

Cluster analysis faces two problems in high dimensions: first, the `curse of dimensionality' that can lead to overfitting and poor generalization performance; and second, the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. In many applications, only a small subset of features provide information about the cluster membership of any one data point, however this informative feature subset may not be the same for all data points... (read more)

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