CDF Transform-Shift: An effective way to deal with inhomogeneous density datasets

5 Oct 2018 Ye Zhu Kai Ming Ting Mark Carman Maia Angelova

Many distance-based algorithms exhibit bias towards dense clusters in inhomogeneous datasets (i.e., those which contain clusters in both dense and sparse regions of the space). For example, density-based clustering algorithms tend to join neighbouring dense clusters together into a single group in the presence of a sparse cluster; while distance-based anomaly detectors exhibit difficulty in detecting local anomalies which are close to a dense cluster in datasets also containing sparse clusters... (read more)

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