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A Comprehensive Approach to Mode Clustering

Mode clustering is a nonparametric method for clustering that defines clusters using the basins of attraction of a density estimator's modes. We provide several enhancements to mode clustering: (i) a soft variant of cluster assignment, (ii) a measure of connectivity between clusters, (iii) a technique for choosing the bandwidth, (iv) a method for denoising small clusters, and (v) an approach to visualizing the clusters. Combining all these enhancements gives us a complete procedure for clustering in multivariate problems. We also compare mode clustering to other clustering methods in several examples

preprint2015arXivOpen access
Yen-Chi ChenChristopher R. GenoveseLarry Wasserman
MethodologyMachine Learning
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Yen-Chi ChenChristopher R. GenoveseLarry Wasserman

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