Clustering categorical functional data Application to medical discharge letters

Vandewalle, Vincent; Cozma, Cristina; Preda, Cristian

Document type :

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

Title :

Clustering categorical functional data Application to medical discharge letters

Author(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]

Conference title :

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

City :

Londres

Country :

France

Start date of the conference :

2015-12-12

Publication date :

2015-12-14

HAL domain(s) :

Mathématiques [math]

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Peer reviewed article :

Non

Audience :

Internationale

Popular science :

Non

ANR Project :

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

Collections :