Regularization Methods for Machine Learning
Project description
Regularization for Machine Learning
These contents were taugh in summer school RegML 2016 by Lorenzo Rosasco and this GUI in python was submitted as part of final exam.
All the coded and tested functions are in RegML.py and GUIs code structure is in RegML_GUIv2.1.py
Github Page
PyPi -project
Installation
pip install regml
Opening GUI:
import regml
regml.GUI()
Methods
- 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
Kernal Learning
(Linear, Polynomial, Gaussian)
- Linear
- Polynomial
- Gaussian (RBF)
K-Fold Cross Validation
GUI
Using local files
Use these files
- RegML.py
- RegML_GUIv2.1.py
- Getting_Started_Demo.ipynb
Requirments
Following libraries are required to use all the functions in RegML library
- Python(=2.7)
- Numpy(>=1.10.4) Numpy
- Matplotlib(>=0.98) Matplotlib
- Scipy(>=0.12) Optional -(If you need to import .mat data files) Scipy
Tested with following version
GUI is tested on followwing version of libraries
- Python 2.7, 3.7
- Numpy 1.10.4
- Matplotlib 1.15.1
- Scipy 0.17.0
Getting starting with GUI
Windows------------------------
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
Ubuntu/Linux-------------------
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 with DEMO
Getting_Started_Demo is a IPython -Notebook, which can be open in Ipython-Notebook or Jupyter
Notebook
RegML Library
Nikesh Bajaj
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