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Multiview clustering and dimensionality reduction

Project description

Multiview clustering and dimensionality reduction

The multiview package provides multiview methods to work with
multiview data (datasets with several data matrices from the same
samples). It contains methods for multiview dimensionality reduction
and methods for multiview clustering.

Multiview dimensionality reduction

Given a multiview dataset with v input data matrices,multiview
dimensionality reduction methods produce a single, low-dimensional
projection of the input data samples, trying to mantain as much of the
original information as possible.

Package multiview offers the function :doc:`mvmds` to perform multiview
dimensionality reduction in a similar way than the multidimensional scaling
method (cmdscale in R).

Another dimensionality reduction function in this package is :doc:`mvtsne`,
that extends tsne in R to multiview data.

Multiview clustering

Given a multiview dataset with v input data matrices, multiview
clustering methods produce a single clustering assignment, considering
the information from all the input views.
Package multiview offers the function :doc:`mvsc` to perform multiview
spectral clustering. It is an extension to spectral clustering
(in R) to multiview datasets.

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