Metadata-Version: 2.1
Name: JELSR
Version: 0.0.1
Summary: JELSR_Feature_Selection
Home-page: https://github.com/hanhe2018/JELSR
Author: hanhe
Author-email: hanhe@ucdavis.edu
License: UNKNOWN
Description: # JELSR
        Unsupervised Feature Selection of Joint Embedding Sparse Regression Analysis.
        # Summary
        The function JELSR follows the paper "Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection"(2014) by  Chenping Hou, Feiping Nie, Xuelong Li, Dongyun Yi and Yi Wu
        
        # Why a new package
        The JELSR feature selection approach is of great importance and is one of the most popular approaches in feature selection of unsupervised clustering problem.
        
        The Package closely follows the paper and enables users to choose key parameters in the algrithm. It would be helpful to people interested in the method and could be directly applied to numpy array dataset.
        
        The paper is relative new and no existing package designed for JELSR in python yet.
        
        # Reference
        "Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection"(2014) by  Chenping Hou, Feiping Nie, Xuelong Li, Dongyun Yi and Yi Wu
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
