Topological Data Analysis

Posted: 5 Apr 2018

See all articles by Larry Wasserman

Larry Wasserman

Carnegie Mellon University - Department of Statistics

Date Written: March 2018

Abstract

Topological data analysis (TDA) can broadly be described as a collection of data analysis methods that find structure in data. These methods include clustering, manifold estimation, nonlinear dimension reduction, mode estimation, ridge estimation and persistent homology. This paper reviews some of these methods.

Suggested Citation

Wasserman, Larry, Topological Data Analysis (March 2018). Annual Review of Statistics and Its Application, Vol. 5, Issue 1, pp. 501-532, 2018, Available at SSRN: https://ssrn.com/abstract=3156968 or http://dx.doi.org/10.1146/annurev-statistics-031017-100045

Larry Wasserman (Contact Author)

Carnegie Mellon University - Department of Statistics ( email )

Baker Hall
Pittsburgh, PA 15213
United States

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