Comput Methods Programs Biomed - KmL3D: a non-parametric algorithm for clustering joint trajectories.

Tópicos

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Resumo

In cohort studies, variables are measured repeatedly and can be considered as trajectories. A classic way to work with trajectories is to cluster them in order to detect the existence of homogeneous patterns of evolution. Since cohort studies usually measure a large number of variables, it might be interesting to study the joint evolution of several variables (also called joint-variable trajectories). To date, the only way to cluster joint-trajectories is to cluster each trajectory independently, then to cross the partitions obtained. This approach is unsatisfactory because it does not take into account a possible co-evolution of variable-trajectories. KmL3D is an R package that implements a version of k-means dedicated to clustering joint-trajectories. It provides facilities for the management of missing values, offers several quality criteria and its graphic interface helps the user to select the best partition. KmL3D can work with any number of joint-variable trajectories. In the restricted case of two joint trajectories, it proposes 3D tools to visualize the partitioning and then export 3D dynamic rotating-graphs to PDF format.

Resumo Limpo

cohort studi variabl measur repeat can consid trajectori classic way work trajectori cluster order detect exist homogen pattern evolut sinc cohort studi usual measur larg number variabl might interest studi joint evolut sever variabl also call jointvari trajectori date way cluster jointtrajectori cluster trajectori independ cross partit obtain approach unsatisfactori take account possibl coevolut variabletrajectori kmld r packag implement version kmean dedic cluster jointtrajectori provid facil manag miss valu offer sever qualiti criteria graphic interfac help user select best partit kmld can work number jointvari trajectori restrict case two joint trajectori propos d tool visual partit export d dynam rotatinggraph pdf format

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