A Bayesian Approach for Spatial Clustering - IEEE CIS Webinar
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When performing analysis of spatial data, there is often the need to aggregate geographical areas into larger regions, a process called regionalization or spatially constrained clustering. These algorithms assume that the items to be clustered are non-stochastic, an assumption not held in many applications. In this webinar, we discuss these current approaches and also a new probabilistic regionalization algorithm that allows spatially varying random variables as features. Hence, an area highly different from its neighbors can still be considered a member of their cluster if it has a large variance.
- Published on
- November 15, 2016
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