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Clustering Trajectories of a Three-Way Longitudinal Dataset

hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorGettler Summa, Mireille
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorGoldfarb, Bernard
dc.contributor.authorVichi, Maurizio
dc.date.accessioned2023-01-23T09:26:03Z
dc.date.available2023-01-23T09:26:03Z
dc.date.issued2012
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/23798
dc.language.isoenen
dc.subjectMachine Learningen
dc.subjectStatistical Methodsen
dc.subjectData Miningen
dc.subjecttrajectoriesen
dc.subjectT3Clus modelen
dc.subjectSQP algorithmen
dc.subject.ddc519en
dc.titleClustering Trajectories of a Three-Way Longitudinal Dataseten
dc.typeChapitre d'ouvrage
dc.description.abstractenLongitudinal data are widely used information for repeated observations of the same units over a period of time in order to investigate developmental trends across life span of units. Each object depicts, in the space of the features and of time, a trajectory describing its changes over time. Here trajectories are modeled according to three features: trend, velocity and acceleration. Clustering trajectories of a longitudinal data set is an important issue to assess similarities in the histories of the observed units that we fully discuss in this chapter. Starting from the Tucker model, widely used in psychometrics, we consider the optimal partition of trajectories that minimizes a distance accounting for trend, for velocity and for acceleration of trajectories. A Sequential Quadratic Programming algorithm is proposed to solve the clustering problem and its performance is evaluated by simulationen
dc.identifier.citationpages243en
dc.relation.ispartofseriestitleComputer science and data analysis seriesen
dc.relation.ispartoftitleStatistical Learning and Data Scienceen
dc.relation.ispartofeditorMireille Gettler Summa, Leon Bottou, Bernard Goldfarb, Fionn Murtagh, Catherine Pardoux, Myriam Touati
dc.relation.ispartofpublnameRoutledgeen
dc.relation.ispartofpublcityLondonen
dc.relation.ispartofdate2012
dc.relation.ispartofpages243en
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.ispartofisbn978-1-4398-6763-1en
dc.relation.forthcomingnonen
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dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2023-01-23T09:20:20Z
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