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A CHAID tree building algorithm

Project description

========================================
Chi-Squared Automatic Inference Detection
========================================

This package provides a python implementation of the Chi-Squared Automatic Inference Detection (CHAID) decision tree. More details can be found here_.


Installation
------------

CHAID is distributed via pypi_ and can be installed like:

.. code-block:: bash

pip install CHAID


Creating a Tree
---------------

.. code-block:: python

import CHAID from CHAID

pandas_data_frame = ...
independent_variable_columns = ['a', 'b', 'c']
dep_variable = ['d']
CHAID.from_pandas_df(df, independent_variable_columns, dep_variable)

Running from the Command Line
-----------------------------

You can play around with the repo by cloning and running this from the command line:

.. code-block:: bash

python3 -m CHAID CHAID/data/titanic.csv survived sex embarked --max-depth 4 --min-samples 2 --alpha-merge 0.05

It calls the `print_tree()` method, which prints the tree to terminal:

.. code-block:: bash

([], {'1': 500.0, '0': 809.0}, embarked, 1.0, 0.31731050786291404)
├── (['C', 'Q'], {'1': 194.0, '0': 199.0}, None, None, 1)
└── (['S', '<missing>'], {'1': 306.0, '0': 610.0}, None, None, 1)

To get a LibTree object, call to_tree() on the CHAID instance

.. _here: http://www.python.org/
.. _pypi: https://en.wikipedia.org/wiki/CHAID

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