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        "author": "Mar\u00eda Araceli Burgue\u00f1o Caballero",
        "author_email": "mburgueno@uoc.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Environment :: Other Environment",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "Multiview clustering and dimensionality reduction\n    \n    The multiview package provides multiview methods to work with\n    multiview data (datasets with several data matrices from the same\n    samples). It contains methods for multiview dimensionality reduction\n    and methods for multiview clustering.\n\n    Multiview dimensionality reduction\n    \n    Given a multiview dataset with v input data matrices,multiview\n    dimensionality reduction methods produce a single, low-dimensional\n    projection of the input data samples, trying to mantain as much of the\n    original information as possible.\n\n    Package multiview offers the function :doc:`mvmds` to perform multiview\n    dimensionality reduction in a similar way than the multidimensional scaling\n    method (cmdscale in R).\n\n    Another dimensionality reduction function in this package is :doc:`mvtsne`,\n    that extends tsne in R to multiview data.\n\n    Multiview clustering\n    \n    Given a multiview dataset with v input data matrices, multiview\n    clustering methods produce a single clustering assignment, considering\n    the information from all the input views.\n    Package multiview offers the function :doc:`mvsc` to perform multiview\n    spectral clustering. It is an extension to spectral clustering\n    (in R) to multiview datasets.",
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        "keywords": "multiview,clustering,dimensionality reduction",
        "license": "",
        "maintainer": "",
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        "name": "multiview",
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        "summary": "Multiview clustering and dimensionality reduction",
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