semvec/pypi-packages huggingface dataset:
multiview 1.0
Multiview clustering and dimensionality reduction
Keywords: multiview,clustering,dimensionality reduction

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.