Copula Archetypal Analysis

Kaufmann, Dinu and Keller, Sebastian and Roth, Volker. (2015) Copula Archetypal Analysis. In: Pattern Recognition. pp. 117-128.

[img] PDF - Published Version
Restricted to Repository staff only


Official URL: http://edoc.unibas.ch/53150/

Downloads: Statistics Overview


We present an extension of classical archetypal analysis (AA). It is motivated by the observation that classical AA is not invariant against strictly monotone increasing transformations. Establishing such an invariance is desirable since it makes AA independent of the chosen measure: representing a data set in meters or log(meters) should lead to approximately the same archetypes. The desired invariance is achieved by introducing a semi-parametric Gaussian copula. This ensures the desired invariance and makes AA more robust against outliers and missing values. Furthermore, our framework can deal with mixed discrete/continuous data, which certainly is the most widely encountered type of data in real world applications. Since the proposed extension is presented in form of a preprocessing step, updating existing classical AA models is especially effortless.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Datenanalyse (Roth)
UniBasel Contributors:Roth, Volker and Kaufmann, Dinu and Keller, Sebastian Mathias
Item Type:Book Section, refereed
Book Section Subtype:Further Contribution in a Book
Series Name:Lecture Notes in Computer Science
Issue Number:9358
Note:Publication type according to Uni Basel Research Database: Book item
Related URLs:
Identification Number:
edoc DOI:
Last Modified:04 Oct 2017 13:38
Deposited On:04 Oct 2017 13:35

Repository Staff Only: item control page