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Reproducible Logistic Regression on Fisher's Iris Flower Database

This bundle contains the code I used to generate the tables on the paper:

@inproceedings{bob2012,
  author = {John Doe},
  title = {A Simple Solution to Iris Flower Classification},
  year = {2015},
  month = jun,
  booktitle = {Reproducible Research Conference, Rio de Janeiro, 2015},
  url = {http://example.com/path/to/my/article.pdf},
}

We appreciate your citation in case you use results obtained directly or indirectly via this software package.

Installation

Run:

$ python bootstrap-buildout.py
$ ./bin/buildout

The tests on my paper were executed on a machine running Ubuntu 12.04, with Python versions 2.6, 2.7, 3.3 and 3.4, providing the same results.

Running

I have created a script that can run the source code reproducing all tables from the above paper. Run it like so:

$ ./bin/paper.py

The contents of each table in the paper should be printed one after the other.

Troubleshooting

You can run unit tests I have prepared like this:

$ ./bin/nosetests

In case of problems, please get in touch with me by e-mail.

Licensing

This work is licensed under the GPLv3.

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Basic example of a Reproducible Research Project in Python.

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