https://github.com/nickgeneva/kernel_smoothers

Tutorials on kernel smoothing techniques
https://github.com/nickgeneva/kernel_smoothers

kernel-methods kernel-smoothing machine-learning machine-learning-algorithms

Last synced: 20 days ago
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Tutorials on kernel smoothing techniques

• Host: GitHub
• URL: https://github.com/nickgeneva/kernel_smoothers
• Owner: NickGeneva
• License: mit
• Created: 2019-04-23T01:01:56.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-05-01T13:38:43.000Z (over 5 years ago)
• Last Synced: 2024-12-02T19:52:35.504Z (about 1 month ago)
• Topics: kernel-methods, kernel-smoothing, machine-learning, machine-learning-algorithms
• Language: Jupyter Notebook
• Homepage:
• Size: 21.7 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Kernel Smoothers

Spring 2019 AME-70790 Final Project

Nicholas Geneva (ngeneva at nd.edu, [@NickGeneva](https://twitter.com/NickGeneva))

Reference: Wand, M. P., & Jones, M. C. (1994). Kernel smoothing. Chapman and Hall/CRC.

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![multivariate_regression](figs/08_multivariate_regression.png)

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Various demo files written in python to illustrate the fundementials of kernel smoothers and kernel methods. This files were written as a part of class final project in Spring 2019.

Click on the following links to view each notebook:

1. [01_kernel_bandwidth.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/01_kernel_bandwidth.ipynb)

2. [02_kernel_shape.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/02_kernel_shape.ipynb)

3. [03_multivariate_kernel.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/03_multivariate_kernel.ipynb)

4. [04_chicago_crime_density.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/04_chicago_crime_density.ipynb)

5. [05_local_linear_regression.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/05_local_linear_regression.ipynb)

6. [06_local_quadratic_regression.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/06_local_quadratic_regression.ipynb)

7. [07_nadaraya_watson_regression.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/07_nadaraya_watson_regression.ipynb)

8. [08_multivariate_regression.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/08_multivariate_regression.ipynb)

9. [09_scottish_hill_races.ipynb](https://nbviewer.jupyter.org/github/AbsoluteStratos/kernel_smoothers/blob/master/09_scottish_hill_races.ipynb)

#### Note:

If the Jupyter notebooks do not show on github you can view the rendered version at [nbviewer.org](https://nbviewer.jupyter.org/). Simply paste the respective notebook url into the prompt and it will be executed.