{"id":34106888,"url":"https://github.com/nikeshbajaj/regularization_for_machine_learning","last_synced_at":"2026-04-11T05:01:09.782Z","repository":{"id":57460901,"uuid":"107844831","full_name":"Nikeshbajaj/Regularization_for_Machine_Learning","owner":"Nikeshbajaj","description":"Regularization for Machine Learning-RegML GUI","archived":false,"fork":false,"pushed_at":"2022-12-03T04:17:48.000Z","size":791,"stargazers_count":6,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-12-17T01:12:07.481Z","etag":null,"topics":["gaussian","gui","kernel","kernel-methods","machine-learning","polynomial","regularization","svd"],"latest_commit_sha":null,"homepage":"https://nikeshbajaj.github.io/Regularization_for_Machine_Learning/","language":"Jupyter 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Notebook","readme":"# Regularization methods for machine learning\n### These contents were taugh in summer school [**RegML 2016**](http://lcsl.mit.edu/courses/regml/regml2016/) by [Lorenzo Rosasco](http://web.mit.edu/lrosasco/www/) and this GUI in python was submitted as part of final exam.\n\n[![DOI](https://zenodo.org/badge/107844831.svg)](https://zenodo.org/badge/latestdoi/107844831)\n\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![PyPI version fury.io](https://badge.fury.io/py/regml.svg)](https://pypi.org/project/regml/)\n[![PyPI pyversions](https://img.shields.io/pypi/pyversions/regml.svg)](https://pypi.python.org/pypi/regml/)\n[![GitHub release](https://img.shields.io/github/release/nikeshbajaj/Regularization_for_Machine_Learning.svg)](https://github.com/Nikeshbajaj/Regularization_for_Machine_Learning/releases/)\n[![PyPI format](https://img.shields.io/pypi/format/regml.svg)](https://pypi.python.org/pypi/regml/)\n[![PyPI implementation](https://img.shields.io/pypi/implementation/regml.svg)](https://pypi.python.org/pypi/regml/)\n[![HitCount](http://hits.dwyl.io/nikeshbajaj/regml.svg)](http://hits.dwyl.io/nikeshbajaj/regml)\n![GitHub commit activity](https://img.shields.io/github/commit-activity/y/nikeshbajaj/Regularization_for_Machine_Learning?style=plastic)\n[![Percentage of issues still open](http://isitmaintained.com/badge/open/nikeshbajaj/Regularization_for_Machine_Learning.svg)](http://isitmaintained.com/project/nikeshbajaj/Regularization_for_Machine_Learning \"Percentage of issues still open\")\n\n\n[![PyPI download month](https://img.shields.io/pypi/dm/regml.svg)](https://pypi.org/project/regml/)\n[![PyPI download week](https://img.shields.io/pypi/dw/regml.svg)](https://pypi.org/project/regml/)\n\n[![Generic badge](https://img.shields.io/badge/pip%20install-regml-blue.svg)](https://pypi.org/project/regml/)\n[![Ask Me Anything !](https://img.shields.io/badge/Ask%20me-anything-1abc9c.svg)](mailto:n.bajaj@qmul.ac.uk)\n\n![PyPI - Downloads](https://img.shields.io/pypi/dm/regml?style=social)\n\nTotal: [![PyPI download total](https://static.pepy.tech/personalized-badge/regml?period=total\u0026units=international_system\u0026left_color=black\u0026right_color=orange\u0026left_text=downloads)](https://pepy.tech/project/regml)\n\n#### All the coded and tested functions are in [RegML.py](https://github.com/Nikeshbajaj/Regularization_for_Machine_Learning/blob/master/RegML.py) and GUIs code structure is in [RegML_GUIv2.1.py](https://github.com/Nikeshbajaj/Regularization_for_Machine_Learning/blob/master/RegML_GUIv2.1.py)\n\n## [Github Page](https://nikeshbajaj.github.io/Regularization_for_Machine_Learning/)\n## [PyPi -project](https://pypi.org/project/regml/)\n\n## Installation\n```\npip install regml\n```\n\n## Opening GUI:\n\n```\nimport regml\nregml.GUI()\n\n```\n\n\n### Regularization Methods\n* Regularized Least Squares -RLS [Referance](https://en.wikipedia.org/wiki/Regularized_least_squares)\n* Nu-Method [Referance]()\n* Iterative Landweber Method [Referance](https://en.wikipedia.org/wiki/Landweber_iteration)\n* Singular Value Decomposition [Reference](https://en.wikipedia.org/wiki/Singular-value_decomposition)\n* Trunctated SVD [Referance 1](http://arxiv.org/pdf/0909.4061) [Referance 2](http://langvillea.people.cofc.edu/DISSECTION-LAB/Emmie%27sLSI-SVDModule/p5module.html)\n* Spectral cut-off\n\n### Kernal Learning \n(Linear, Polynomial, Gaussian)\n* **Linear**: $K(X,Y) = X'Y$ \n  * ![equation1](http://latex.codecogs.com/gif.latex?%5Clarge%20K%28X%2CY%29%20%3D%20X%5ETY)\n* **Polynomial**: $K(X,Y) = (X'Y +1)^p$ \n  * ![equation2](http://latex.codecogs.com/gif.latex?%5Clarge%20K%28X%2CY%29%20%3D%20%28X%5ET%20Y%20+%201%29%5Ep)\n* **Gaussian (RBF)**: $K(X,Y) = exp(-||X-Y||^2/2\\sigma^2)$ \n  * ![equation3](https://latex.codecogs.com/gif.latex?K%28X%2CY%29%20%3D%20exp%28-%7C%7CX-Y%7C%7C%5E2/2%5Csigma%5E2%29)\n  \n\n### **K-Fold Cross Validation**\n\n## GUI\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/Nikeshbajaj/Regularization_for_Machine_Learning/master/images/GUI_Win_Lin.jpg\" width=\"800\"/\u003e\n\u003c/p\u003e\n\n# Regularization for Machine Learning\n---\n## Files\n1. RegML.py\n2. RegML_GUIv2.1.py\n3. Getting_Started_Demo.ipynb\n\n## Requirments \n### Following libraries are required to use all the functions in RegML library\n1. Python(=2.7)     \n2. Numpy(\u003e=1.10.4)     [Numpy](https://pypi.python.org/pypi/numpy) \n3. Matplotlib(\u003e=0.98)  [Matplotlib](https://github.com/matplotlib/matplotlib) \n4. Scipy(\u003e=0.12)       Optional -(If you need to import .mat data files)  [Scipy](https://www.scipy.org/install.html) \n\n## Tested with following version\nGUI is tested on followwing version of libraries\n* Python     2.7 / 3 \n* Numpy      1.10.4\n* Matplotlib 1.15.1\n* Scipy      0.17.0\n\n## Getting starting with GUI\n\n### Windows------------------------\nAfter lauching python, go to directory containing RegML.py and RegML_GUIv2.1.py files and run following command on\npython shell\n```\n\u003e\u003e run RegML_GUIv2.1.py\n```\nIf you are using Spyder or ipython qt, browes to directory, open RegML_GUIv2.1.py file and run it\n\n### Ubuntu/Linux-------------------\n\nOpen terminal, cd to directory contaning all the files and execute following command\n```\n$ python RegML_GUIv2.1.py\n```\nif you have both python 2 and python 3\n\n```\n$ python2 RegML_GUIv2.1.py\n```\n\nIf you are using Spyder or ipython qt, browes to directory, open RegML_GUIv2.1.py file and run it\n\n\n## Getting Started with DEMO\nGetting_Started_Demo is a IPython -Notebook, which can be open in Ipython-Notebook or Jupyter\n\n# [**Notebook**](https://github.com/Nikeshbajaj/Regularization_for_Machine_Learning/blob/master/Getting_Started_Demo.ipynb)\n\n\n# [**RegML Library**](https://github.com/Nikeshbajaj/Regularization_for_Machine_Learning/blob/master/RegML.py)\n\n______________________\n\n# Cite As\n```\n@software{nikesh_bajaj_2019_2646550,\n  author       = {Nikesh Bajaj},\n  title        = {{Nikeshbajaj/Regularization\\_for\\_Machine\\_Learning \n                   0.0.2}},\n  month        = apr,\n  year         = 2019,\n  publisher    = {Zenodo},\n  version      = {0.0.2},\n  doi          = {10.5281/zenodo.2646550},\n  url          = {https://doi.org/10.5281/zenodo.2646550}\n}\n```\n\n\n### Nikesh Bajaj\n\nn.bajaj@qmul.ac.uk\n\nnikesh.bajaj@elios.unige.it\n\n[http://nikeshbajaj.in](http://nikeshbajaj.in)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnikeshbajaj%2Fregularization_for_machine_learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnikeshbajaj%2Fregularization_for_machine_learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnikeshbajaj%2Fregularization_for_machine_learning/lists"}