apyori
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A simple implementation of Apriori algorithm by Python.
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.
- Install with pip :code:
pip install apyori. - 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.pycommand. - If installed, you can also run with :code:
apyori-runcommand.
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