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MagmaClustR
View on CRAN: Click
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Download and install MagmaClustR package within the R console
Install from CRAN:
install.packages("MagmaClustR")
Install from Github:
library("remotes")
install_github("cran/MagmaClustR")
Install by package version:
library("remotes")
install_version("MagmaClustR", "1.2.1")
Attach the package and use:
library("MagmaClustR")
Maintained by
Arthur Leroy
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.MagmaClustR . https://github.com/ArthurLeroy/MagmaClustR/issues . https://github.com/ArthurLeroy/MagmaClustR . https://arthurleroy.github.io/MagmaClustR/ . MagmaClustR results . MagmaClustR.pdf . MagmaClustR_1.2.1.tar.gz . MagmaClustR_1.2.1.zip . MagmaClustR_1.2.1.zip . MagmaClustR_1.2.1.zip . MagmaClustR_1.2.1.tgz . MagmaClustR_1.2.1.tgz . MagmaClustR_1.2.1.tgz . MagmaClustR_1.2.1.tgz . MagmaClustR archive . https://CRAN.R-project.org/package=MagmaClustR .
First Published: 2022-06-06
Latest Update: 2023-05-23
Description:
An implementation for the multi-task Gaussian processes with common
mean framework. Two main algorithms, called 'Magma' and 'MagmaClust',
are available to perform predictions for supervised learning problems, in
particular for time series or any functional/continuous data applications.
The corresponding articles has been respectively proposed by Arthur Leroy,
Pierre Latouche, Benjamin Guedj and Servane Gey (2022)
, and Arthur Leroy, Pierre Latouche,
Benjamin Guedj and Servane Gey (2023) .
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) 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 (classic kernels, training, prediction) of
standard Gaussian processes are also implemented.
How to cite:
Arthur Leroy (2022). MagmaClustR: Clustering and Prediction using Multi-Task Gaussian Processes with Common Mean. R package version 1.2.1, https://cran.r-project.org/web/packages/MagmaClustR. Accessed 10 Jan. 2025.
Previous versions and publish date:
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Other R packages that MagmaClustR depends,
imports, suggests or enhances
Complete documentation for MagmaClustR
Functions, R codes and Examples using
the MagmaClustR R package
Some associated functions: MagmaClustR . chol_inv_jitter . data_allocate_cluster . dmnorm . draw . e_step . elbo_GP_mod_common_hp_k . elbo_clust_multi_GP . elbo_clust_multi_GP_common_hp_i . elbo_monitoring_VEM . expand_grid_inputs . gr_GP . gr_GP_mod . gr_GP_mod_common_hp . gr_GP_mod_common_hp_k . gr_clust_multi_GP . gr_clust_multi_GP_common_hp_i . gr_sum_logL_GP_clust . hp . hyperposterior . hyperposterior_clust . ini_kmeans . ini_mixture . kern_to_cov . kern_to_inv . lin_kernel . list_kern_to_cov . list_kern_to_inv . logL_GP . logL_GP_mod . logL_GP_mod_common_hp . logL_monitoring . m_step . perio_kernel . pipe . plot_db . plot_gif . plot_gp . plot_magmaclust . pred_gif . pred_gp . pred_magma . pred_magmaclust . proba_max_cluster . regularize_data . rq_kernel . sample_gp . se_kernel . select_nb_cluster . simu_db . simu_indiv_se . sum_logL_GP_clust . swimmers . train_gp . train_gp_clust . train_magma . train_magmaclust . update_mixture . ve_step . vm_step . weight .
Some associated R codes: RcppExports.R . data.R . elbos.R . em-magma.R . gradients-elbos.R . gradients-likelihoods.R . initialisation.R . kernel-to-matrices.R . kernels.R . likelihoods.R . package-MagmaClustR.R . plot-functions.R . prediction.R . simulate-data.R . training.R . utils-pipe.R . utils.R . vem-magmaclust.R . Full MagmaClustR package functions and examples
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