Title :

Statistical learning with categorical functional data
Application to pathways of elderly patients after hospitalization. The DAMAGE study.

Author(s) :

Preda, Cristian [Auteur correspondant]
MOdel for Data Analysis and Learning [MODAL]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Gheorghe Mihoc - Caius Iacob Institute of Mathematical Statistics and Applied Mathematics [ISMMA]
Grimonprez, Quentin [Auteur]
DiaGrams Technologies [Lille]

Conference title :

2024 Workshop Center of Mathematical Statistics 60

Conference organizers(s) :

“Gheorghe Mihoc – Caius Iacob” Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy

City :

Bucharest

Country :

Roumanie

Start date of the conference :

2024-10-15

English keyword(s) :

clustering
Categorical functional data analysis
Unsupervised and supervised learning
Principal components

HAL domain(s) :

Statistiques [stat]
Informatique [cs]/Logiciel mathématique [cs.MS]

English abstract : [en]

We introduce unsupervised and supervised models for categorical functional data. Multiple correspondance analysis is extended to functional categorical data and principal components are used as latent variables for clustering ...
Show more >We introduce unsupervised and supervised models for categorical functional data. Multiple correspondance analysis is extended to functional categorical data and principal components are used as latent variables for clustering and regression models. An application on DAMAGE medical dataset is presented.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL