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Basic implementations of machine learning algorithms
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## Overview
Some practical implementations of popular machine learning algorithms.
Data is partially taken from the LIBSVM data sets[1].
### Usage
Running the demo file is easy:
$ python demo.py
This should do it. Make sure NumPy is installed and added to your PYTHONPATH. To check this, type
$ python
and in the Python shell
>> import numpy
if no error occurs, NumPy is installed correctly.
### Currently implemented
* Ridge Regression
### TODO
* fine tuning Ridge Regression
* output validation R.R.
* logistic regression
* SVMs (SMO +variants)
* make test suite
### Links
[1] http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/
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