Metadata-Version: 2.1
Name: delayedsparse
Version: 0.2.1
Summary: Delayed sparse matrix in Python
Home-page: https://github.com/niitsuma/delayedsparse
Author: Hirotaka Niitsuma
Author-email: hirotaka.niitsuma@gmail.com
License: You can use these codes olny for self evaluation. Cannot use these codes for commercial and academical use.
Description: 
        
        ## Delayed Sparse Matrix
        
        Efficient sparse matrix implementation for various "Principal Component Analysis".
        And demo usages of the efficient implementation for 
        
        * Correspondence Analysis(CA) 
        * Principal Component Analysis (PCA)
        * Canonical Correlation Analysis (CCA)
        
        
        To compare with existing methods, you can execute demo.sh.
        ```sh
        >>> bash  demo.sh
        ```
        
        This library is effective when the input matrix size ls large.
        But, in order to demonstrations, the demo programs use only a small matrix.
        You can test more large matrix by setting SIZE variable in demo-*.sh
        
        
        When the input matrix size is large, 
        the program of this library will finish within in few minutes, 
        but the existing methods take hours.
        
        
        
        You can find more general description about CA and PCA in
        https://github.com/MaxHalford/prince
        
        
        ## Installation
        
        **Via PyPI**
        
        ```sh
        >>> pip install delayedsparse
        ```
        
        **Via GitHub for the latest development version**
        
        ```sh
        >>> pip install git+https://github.com/niitsuma/delayedsparse 
        ```
        
        
        ## Requirements
        
        ```sh
        >>> pip3 install sklearn
        ```
        
        In order to execute demo.sh, you need install /usr/bin/time and orange library
        
        ```sh
        >>> apt-get install time
        >>> pip3 install orange
        ```
        
        
        ## License
        
        @2018 Hirotaka Niirtsuma.
        
        
        You can use these codes olny for self evaluation.
        Cannot use these codes for commercial and academical use.
        
        * pantent pending
          * https://patentscope2.wipo.int/search/ja/detail.jsf?docId=JP225380312
          * Japan patent office:patent number 2017-007741
        
        
        
        ## Author
        Hirotaka Niitsuma.
        
        
        @2018 Hirotaka Niirtsuma.
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.4.0
Description-Content-Type: text/markdown
