Metadata-Version: 1.1
Name: apyori
Version: 1.1.1
Summary: Simple Apriori algorithm Implementation.
Home-page: https://github.com/ymoch/apyori
Author: Yu Mochizuki
Author-email: ymoch.dev@gmail.com
License: UNKNOWN
Description: Apyori
        ======
        
        *Apyori* is a simple implementation of
        Apriori algorithm with Python 2.7 and 3.3 - 3.5,
        provided as APIs and as commandline interfaces.
        
        .. image:: https://travis-ci.org/ymoch/apyori.svg?branch=master
            :target: https://travis-ci.org/ymoch/apyori
        .. image:: https://coveralls.io/repos/github/ymoch/apyori/badge.svg?branch=master
            :target: https://coveralls.io/github/ymoch/apyori?branch=master
        
        
        Module Features
        ---------------
        
        - Consisted of only one file and depends on no other libraries,
          which enable you to use it portably.
        - Able to used as APIs.
        
        Application Features
        --------------------
        
        - Supports a JSON output format.
        - Supports a TSV output format for 2-items relations.
        
        
        Installation
        ------------
        
        Choose one from the following.
        
        - Put *apyori.py* into your project.
        - Run :code:`python setup.py install`.
        
        
        API Usage
        ---------
        
        Here is a basic example:
        
        .. code-block:: python
        
            from apyori import apriori
        
            transactions = [
                ['beer', 'nuts'],
                ['beer', 'cheese'],
            ]
            results = list(apriori(transactions))
        
        For more details, see *apyori.apriori* pydoc.
        
        
        CLI Usage
        ---------
        
        First, prepare input data as tab-separated transactions.
        
        - Each item is separated with a tab.
        - Each transactions is separated with a line feed code.
        
        Second, run the application.
        Input data is given as a standard input or file paths.
        
        - Run with :code:`python apyori.py` command.
        - If installed, you can also run with :code:`apyori-run` command.
        
        For more details, use '-h' option.
        
        
        -------
        Samples
        -------
        
        Basic usage
        ***********
        
        .. code-block:: shell
        
            apyori-run < data/integration_test_input_1.tsv
        
        
        Use TSV output
        **************
        
        .. code-block:: shell
        
            apyori-run -f tsv < data/integration_test_input_1.tsv
        
        Fields of output mean:
        
        - Base item.
        - Appended item.
        - Support.
        - Confidence.
        - Lift.
        
        
        Specify the minimum support
        ***************************
        
        .. code-block:: shell
        
            apyori-run -s 0.5 < data/integration_test_input_1.tsv
        
        
        Specify the minimum confidence
        ******************************
        
        .. code-block:: shell
        
            apyori-run -c 0.5 < data/integration_test_input_1.tsv
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
