Metadata-Version: 1.1
Name: sklPCA
Version: 1.0.0
Summary: Supervised Kernel-Based Longitudinal PCA (skl-PCA)
Home-page: http://mindstrong.com
Author: Mindstrong Health Data Science
Author-email: datascience@mindstronghealth.com
License: UNKNOWN
Description: =======
        skl-PCA
        =======
        
        This package implements Supervised Kernel-based Longitudinal Principal Components Analysis (skl-PCA) for predictor dimension reduction in longitudinal models. The software was written by members of the Mindstrong Health Data Science team:
        
            * Patrick Staples, PhD
            * Min Ouyang, PhD
            * Bob Dougherty, PhD
            * Greg Ryslik, PhD, FCAS, MAAA
            * Paul Dagum, MD, PhD
        
        
        Please contact us at `datascience@mindstronghealth.com <datascience@mindstronghealth.com>`_.
        
        NOTE: If you use this software in your work, please cite the following `paper <http://arxiv.org/abs/1808.06638>`_:
        
            Patrick Staples, Min Ouyang, Robert F. Dougherty, Gregory A. Ryslik, and Paul Dagum (2018). Supervised Kernel PCA For Longitudinal Data. http://arxiv.org/abs/1808.06638.
        
        Installation
        ------------
        
        The easiest way to install the package is via ``easy_install`` or ``pip``::
        
            $ pip install sklPCA
        
        This should also take care of the dependencies (numpy, scipy, pandas, and sklearn).
        
        Usage
        -----
        
        See examples.py for examples of simulated data, predictor reduction, fitting, and cross-validated model performance.
        
        
        Copyright & License
        -------------------
        
        Copyright (c) 2018, `Mindstrong Health <http://mindstronghealth.com>`_. GNU Affero General Public License.
        
        
Keywords: digital biomarkers,supervised methods,kernel methods,longitudinal methods,dimension reduction,machine learning
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Programming Language :: Python :: 3
