Total:

pip install regml

import regml
regml.GUI()

• Regularized Least Squares -RLS Referance
• Nu-Method Referance
• Iterative Landweber Method Referance
• Singular Value Decomposition Reference
• Trunctated SVD Referance 1 Referance 2
• Spectral cut-off

(Linear, Polynomial, Gaussian)

• Linear: $K(X,Y) = X'Y$
  • 
• Polynomial: $K(X,Y) = (X'Y +1)^p$
  • 
• Gaussian (RBF): $K(X,Y) = exp(-||X-Y||^2/2\sigma^2)$
  • 

1. RegML.py
2. RegML_GUIv2.1.py
3. Getting_Started_Demo.ipynb

1. Python(=2.7)
2. Numpy(>=1.10.4) Numpy
3. Matplotlib(>=0.98) Matplotlib
4. Scipy(>=0.12) Optional -(If you need to import .mat data files) Scipy

GUI is tested on followwing version of libraries

• Python 2.7 / 3
• Numpy 1.10.4
• Matplotlib 1.15.1
• Scipy 0.17.0

After lauching python, go to directory containing RegML.py and RegML_GUIv2.1.py files and run following command on python shell

>> run RegML_GUIv2.1.py

If you are using Spyder or ipython qt, browes to directory, open RegML_GUIv2.1.py file and run it

Open terminal, cd to directory contaning all the files and execute following command

$ python RegML_GUIv2.1.py

if you have both python 2 and python 3

$ python2 RegML_GUIv2.1.py

If you are using Spyder or ipython qt, browes to directory, open RegML_GUIv2.1.py file and run it

Getting_Started_Demo is a IPython -Notebook, which can be open in Ipython-Notebook or Jupyter

@software{nikesh_bajaj_2019_2646550,
  author       = {Nikesh Bajaj},
  title        = {{Nikeshbajaj/Regularization\_for\_Machine\_Learning 
                   0.0.2}},
  month        = apr,
  year         = 2019,
  publisher    = {Zenodo},
  version      = {0.0.2},
  doi          = {10.5281/zenodo.2646550},
  url          = {https://doi.org/10.5281/zenodo.2646550}
}

n.bajaj@qmul.ac.uk

nikesh.bajaj@elios.unige.it

http://nikeshbajaj.in