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Uniform Cross-entropy Clustering

Publication date: 24.03.2017

Schedae Informaticae, 2016, Volume 25, pp. 117 - 126

https://doi.org/10.4467/20838476SI.16.009.6190

Authors

,
Maciej Brzeski
TensorCell
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
All publications →
Przemysław Spurek
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
https://orcid.org/https://orcid.org/0000-0003-0097-5521 Orcid
All publications →

Titles

Uniform Cross-entropy Clustering

Abstract

Robust mixture models approaches, which use non-normal distributions have recently been upgraded to accommodate data with fixed bounds. In this article we propose a new method based on uniform distributions and Cross-Entropy Clustering (CEC). We combine a simple density model with a clustering method which allows to treat groups separately and estimate parameters in each cluster individually. Consequently, we introduce an effective clustering algorithm which deals with non-normal data.

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Information

Information: Schedae Informaticae, 2016, Volume 25, pp. 117 - 126

Article type: Original article

Titles:

Polish:

Uniform Cross-entropy Clustering

English:

Uniform Cross-entropy Clustering

Authors

TensorCell

Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland

https://orcid.org/https://orcid.org/0000-0003-0097-5521

Przemysław Spurek
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
https://orcid.org/https://orcid.org/0000-0003-0097-5521 Orcid
All publications →

Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland

Published at: 24.03.2017

Article status: Open

Licence: None

Percentage share of authors:

Maciej Brzeski (Author) - 50%
Przemysław Spurek (Author) - 50%

Article corrections:

-

Publication languages:

English

View count: 2132

Number of downloads: 1797

<p> Uniform Cross-entropy Clustering</p>