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Assessment of probability density estimation methods: Parzen window and finite Gaussian mixtures

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Archambeau, Cédric [UCL] Valle, M. [Universita degli studi di Genova - DIBE] Assenza, A. [Universita degli studi di Genova - DIPTEM] Verleysen, Michel [UCL]

Probability density function (PDF) estimation is a very critical task in many applications of data analysis. For example in the Bayesian framework decisions are taken according to Bayes' rule, which directly involves the evaluation of the PDF. Many methods are available to this aim, but there is no consensus in the literature about which to use, nor about the pros and cons of each of them. In this paper, we present a thorough and extensive experimental comparison between two of the most popular methods: Parzen window and finite Gaussian mixture. Extended experimental results and application development guidelines are reported.

Document type Communication à un colloque (Conference Paper) – Présentation orale avec comité de sélection
Access type Accès restreint
Publication date 2006
Language Anglais
Conference "IEEE International Symposium on Circuits and Systems (ISCAS 2006)", Island of Kos (Greece) (du 21/05/2006 au 24/05/2006)
Host document "Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS 2006)"- 3245-3248 (ISBN : 0-7803-9389-9)
Publisher IEEE
Affiliation UCL - Autre
Links
Bibliographic reference Archambeau, Cédric ; Valle, M. ; Assenza, A. ; Verleysen, Michel. Assessment of probability density estimation methods: Parzen window and finite Gaussian mixtures.IEEE International Symposium on Circuits and Systems (ISCAS 2006) (Island of Kos (Greece), du 21/05/2006 au 24/05/2006). In: Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS 2006), IEEE2006, p.3245-3248
Permanent URL http://hdl.handle.net/2078.1/67923