Classification croisée et modèles

Y. Bencheikh

RAIRO - Operations Research (2010)

  • Volume: 33, Issue: 4, page 525-541
  • ISSN: 0399-0559

Abstract

top
The relations between automatic clustering methods and inferentiel statistical models have mostely been studied when the data involves only one set. We propose to study these relations in the case of data involving two sets. We shall look at cross clustering methods as suggested by Govaert [6]; we show that these methods, like the simple clustering methods, can be considered as a clustering approach of a mixture model. We introduce the notion of crossed mixture from a concret example and define the notions of likelihood and associated clustered likelihood. Then, we study the relations which exist between the crossed mixture models and simple models and we show that these relations are completely similar to those which exist between the crossed clustering methods and simple clustering methods.

How to cite

top

Bencheikh, Y.. "Classification croisée et modèles." RAIRO - Operations Research 33.4 (2010): 525-541. <http://eudml.org/doc/197807>.

@article{Bencheikh2010,
abstract = { The relations between automatic clustering methods and inferentiel statistical models have mostely been studied when the data involves only one set. We propose to study these relations in the case of data involving two sets. We shall look at cross clustering methods as suggested by Govaert [6]; we show that these methods, like the simple clustering methods, can be considered as a clustering approach of a mixture model. We introduce the notion of crossed mixture from a concret example and define the notions of likelihood and associated clustered likelihood. Then, we study the relations which exist between the crossed mixture models and simple models and we show that these relations are completely similar to those which exist between the crossed clustering methods and simple clustering methods. },
author = {Bencheikh, Y.},
journal = {RAIRO - Operations Research},
keywords = { L1 distance; automatic clustering; mixture; cross mixture. ; L1 distance; crossed mixture},
language = {eng},
month = {3},
number = {4},
pages = {525-541},
publisher = {EDP Sciences},
title = {Classification croisée et modèles},
url = {http://eudml.org/doc/197807},
volume = {33},
year = {2010},
}

TY - JOUR
AU - Bencheikh, Y.
TI - Classification croisée et modèles
JO - RAIRO - Operations Research
DA - 2010/3//
PB - EDP Sciences
VL - 33
IS - 4
SP - 525
EP - 541
AB - The relations between automatic clustering methods and inferentiel statistical models have mostely been studied when the data involves only one set. We propose to study these relations in the case of data involving two sets. We shall look at cross clustering methods as suggested by Govaert [6]; we show that these methods, like the simple clustering methods, can be considered as a clustering approach of a mixture model. We introduce the notion of crossed mixture from a concret example and define the notions of likelihood and associated clustered likelihood. Then, we study the relations which exist between the crossed mixture models and simple models and we show that these relations are completely similar to those which exist between the crossed clustering methods and simple clustering methods.
LA - eng
KW - L1 distance; automatic clustering; mixture; cross mixture. ; L1 distance; crossed mixture
UR - http://eudml.org/doc/197807
ER -

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

                
Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.