https://github.com/bambooom/multi-linrg

https://github.com/bambooom/multi-linrg

Last synced: about 1 month ago
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• Host: GitHub
• URL: https://github.com/bambooom/multi-linrg
• Owner: bambooom
• Created: 2016-02-12T14:36:46.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2016-02-12T15:24:08.000Z (almost 9 years ago)
• Last Synced: 2023-03-06T18:45:22.402Z (almost 2 years ago)
• Language: Jupyter Notebook
• Size: 22.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## multivariate linear regression

`y = w0 + w1 * x1 + w2 * x2 + w3 * x3`

* Use two methods to calculate w0,w1,w2,w3:

  * Explicit analytical solution by matrix: ols_matrix

    * 公式 [ols wiki](https://en.wikipedia.org/wiki/Ordinary_least_squares)

    * 原理是使SRR最小化, 得到的是 ols estimator

  * stochastic gradient descent: sgd

    * 参考 [Andrew Ng 的 notes](http://cs229.stanford.edu/notes/cs229-notes1.pdf)

* files:

  * 数据: `data.csv`

  * 开发文档: [multi-linrg.ipynb](https://github.com/bambooom/multi-linrg/blob/master/multi-linrg.ipynb)

  * 代码: [multi-linrg.py](https://github.com/bambooom/multi-linrg/blob/master/multi-linrg.py)

* Solutions:

```

1st method - analytical solution by matrix

w0 = 2.030762

w1 = 2.973967

w2 = -0.541390

w3 = 0.971329

2nd method - stochastic gradient descent

w0 = 2.030762

w1 = 2.973971

w2 = -0.541381

w3 = 0.971339

```