marknabil / B31XI-SI-Features-Normalisation

Practise of Pattern Recignition tackling the problematic of Features Normalisation

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SI - Pattern Recognition

Table-of-contents

More description is given in the subsections.

Dependencies

The following practise has been tested with Ubuntu 14.04.

In order to use the Ipython Notebook, the following dependencies are needed:

  • IPython - sudo apt-get install ipython
  • IPython notebook - sudo apt-get install ipython-notebook
  • Numpy - sudo apt-get install python-numpy
  • Matplotlib - sudo apt-get install python-matplotlib
  • Scikit-learn - sudo apt-get install python-sklearn

We strongly recommend to use a Linux environment to perform this practise.

Features normalization

The following module of the framework will be studied: Alt text

Synthetic data will be generated. Simple classification using Leave-One-Patient-Out cross-validation will be performed in order to show the importance of features normalization previous to classification.

To perform the practise

Assignment procedure

In order to perform the practise, you will have to fork the current project. To do so,

  • Fork the current project by click on the Fork icon Do not fine the icon,
  • Select your GitHub profile if necessary,
  • Clone the repository Do not fine the icon,
  • Solve the practise by executing the Ipython notebook,
  • Commit & push your changes in your own repository,
  • Make a pull request.

Execute the Ipython notebook

Enter the following command in a terminal ipython notebook.

This command should run the server locally via your default web browser and you will be able to play with the notebook.

If you are just curious to see what the ipython notebook look like, you can view it there.

Enjoy!!!

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Practise of Pattern Recignition tackling the problematic of Features Normalisation

License:GNU General Public License v2.0