supervised: Supervised Multiblock Methods

In multiblock: Multiblock Data Fusion in Statistics and Machine Learning

Supervised Multiblock Methods

Description

Collection of supervised multiblock methods:

• MB-PLS - Multiblock Partial Least Squares (mbpls)

• sMB-PLS - Sparse Multiblock Partial Least Squares (smbpls)

• SO-PLS - Sequential and Orthogonalized PLS (sopls)

• PO-PLS - Parallel and Orthogonalized PLS (popls)

• ROSA - Response Oriented Sequential Alternation (rosa)

• mbRDA - Multiblock Redundancy Analysis (mbrda)

See Also

Overviews of available methods, multiblock, and methods organised by main structure: basic, unsupervised, asca, supervised and complex. Common functions for computation and extraction of results and plotting are found in multiblock_results and multiblock_plots, respectively.

Examples

data(potato)
mb <- mbpls(Sensory ~ Chemical + Compression, data=potato, ncomp = 5)
print(mb)

# Convert data.frame with AsIs objects to list of matrices
potatoList <- lapply(potato, unclass)
mbr <- mbrda(Sensory ~ Chemical + Compression, data=potatoList, ncomp = 10)
print(mbr)
scoreplot(mbr, labels="names")

multiblock documentation built on Nov. 18, 2023, 5:06 p.m.