Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 12, Number 2 (2018), 4288-4312.
Analysis of a mode clustering diagram
Mode-based clustering methods define clusters in terms of the modes of a density estimate. The most common mode-based method is mean shift clustering which defines clusters to be the basins of attraction of the modes. Specifically, the gradient of the density defines a flow which is estimated using a gradient ascent algorithm. Rodriguez and Laio (2014) introduced a new method that is faster and simpler than mean shift clustering. Furthermore, they define a clustering diagram that provides a simple, two-dimensional summary of the clustering information. We study the statistical properties of this diagram and we propose some improvements and extensions. In particular, we show a connection between the diagram and robust linear regression.
Electron. J. Statist., Volume 12, Number 2 (2018), 4288-4312.
Received: May 2018
First available in Project Euclid: 18 December 2018
Permanent link to this document
Digital Object Identifier
Verdinelli, Isabella; Wasserman, Larry. Analysis of a mode clustering diagram. Electron. J. Statist. 12 (2018), no. 2, 4288--4312. doi:10.1214/18-EJS1510. https://projecteuclid.org/euclid.ejs/1545123625