MagmaClustR

The MagmaClustR package implements two main algorithms, called Magma and MagmaClust, using a multi-task Gaussian processes (GP) model to perform predictions for supervised learning problems. Applications involving functional data, such as multiple time series, are particularly well-handled. Theses approaches leverage the learning of cluster-specific mean processes, which are common across similar tasks, to provide enhanced prediction performances (even far from data points) at a linear computational cost (in the number of tasks). MagmaClust is a generalisation of Magma where the tasks are simultaneously clustered into groups, each being associated to a specific mean process. User-oriented functions in the package are decomposed into training, prediction and plotting functions. Some basic features of standard GPs are also implemented.