Clustering categorical functional data Application to medical discharge letters

Vandewalle, Vincent; Cozma, Cristina; Preda, Cristian

Type de document :

Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes: Conférence invitée

Titre :

Clustering categorical functional data Application to medical discharge letters

Auteur(s) :

Vandewalle, Vincent [Auteur]

MOdel for Data Analysis and Learning [MODAL]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Cozma, Cristina [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Preda, Cristian [Auteur]

Laboratoire Paul Painlevé - UMR 8524 [LPP]
MOdel for Data Analysis and Learning [MODAL]

Titre de la manifestation scientifique :

8th International Conference of the ERCIM WG on Computational and Methodological Statistics

Ville :

Londres

Pays :

France

Date de début de la manifestation scientifique :

2015-12-12

Date de publication :

2015-12-14

Discipline(s) HAL :

Mathématiques [math]

Résumé en anglais : [en]

Categorical functional data represented by paths of a stochastic jump process are considered for clustering. For paths of the same length, the extension of the multiple correspondence analysis allows the use of well-known ...
Lire la suite >Categorical functional data represented by paths of a stochastic jump process are considered for clustering. For paths of the same length, the extension of the multiple correspondence analysis allows the use of well-known methods for clustering finite dimensional data. When the paths are of different lengths, the analysis is more complex. In this case, for Markov models we propose an EM algorithm to estimate a mixture of Markov processes. A simulation study as well as a real application on hospital stays will be presented.Lire moins >

Langue :

Anglais

Comité de lecture :

Non

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

Optimisation de la prise en Charge des Patients à l'Hôpital

Collections :