PyMEF - A framework for exponential families in Python

Modeling data is often a critical step in many challenging applications in computer vision, bioinformatics or machine learning. Gaussian Mixture Models are a popular choice in many applications. Although these mixtures are powerful enough to approximate complex distributions, they may not be the bes...

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Bibliographische Detailangaben
Hauptverfasser: Schwander, O., Nielsen, F.
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Modeling data is often a critical step in many challenging applications in computer vision, bioinformatics or machine learning. Gaussian Mixture Models are a popular choice in many applications. Although these mixtures are powerful enough to approximate complex distributions, they may not be the best choice for some applications. Usual software mixtures libraries are often limited to a particular kind of distribution, which makes difficult to change the distribution and so to choose the best one. In this paper we focus on a particular class of distributions, the exponential families (which contains a lot of usual distributions like Gaussian, Rayleigh or Gamma). We present pyMEF, a Python framework to manipulate, learn and simplify mixtures of exponential families.
ISSN:2373-0803
2693-3551
DOI:10.1109/SSP.2011.5967790