ITCS 6162
Group 2

"Attribute Selection in Decision Trees"

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# BACKGROUND #
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This code demonstrates the ID3 method for
attribute selection and generating a decision tree.

This code uses the standard "Tennis" training dataset
originally presented by J. Ross Quinlan
in "Induction of Decision Trees"
(Machine Language, Vol. 1, Issue 1, March 1986, pp. 81-106).

The code is designed as a demo, and works with
a supplied data file. For a more flexible version,
certain hard-coded values could be modified so as
to be supplied by the user. These are noted in the code.

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# VERSION INFORMATION #
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This code was developed with Python 3.9.9
on Mac OS X 12.2.1 (Monterey)

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# DEPENDENCIES #
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This program requires the Pandas library,
Which can be installed via pip, by running
`pip install pandas`

For more information, see the following:
https://pypi.org/project/pandas/
https://pandas.pydata.org/docs/getting_started/install.html

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# RUNNING THE CODE #
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The code can be run by executing the file ID3_Demo.py
along with the path to the data input file, as follows:

python ./ID3_Demo.py ./Tennis_Data.csv

The program will perform attribute selection using the
Maximum Information Gain method, and will print out
a simple graphical depiction of the decision tree.
