https://github.com/drsoliddevil/mlr-gd

Multiple linear regression by gradient descent.
https://github.com/drsoliddevil/mlr-gd

data-science gradient-descent linear-regression machine-learning ml numpy python regression

Last synced: 1 day ago
JSON representation

Multiple linear regression by gradient descent.

• Host: GitHub
• URL: https://github.com/drsoliddevil/mlr-gd
• Owner: DrSolidDevil
• License: bsd-3-clause
• Created: 2025-01-09T16:02:55.000Z (27 days ago)
• Default Branch: main
• Last Pushed: 2025-02-03T21:15:50.000Z (2 days ago)
• Last Synced: 2025-02-03T21:34:15.717Z (2 days ago)
• Topics: data-science, gradient-descent, linear-regression, machine-learning, ml, numpy, python, regression
• Language: Python
• Homepage: https://pypi.org/project/mlr-gd/
• Size: 102 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
 


  

  





Multiple linear regression by gradient descent.





Disclaimer:

This code is very early on and my first proper attempt to create a package so things may be a bit weird/not up to standard.








Installation


To install mlr-gd you can use [pip](https://pip.pypa.io):

```bash

$ python -m pip install mlr-gd

```

Alternatively, you can install it by cloning the [GitHub repository](https://github.com/DrSolidDevil/mlr-gd):

```bash

$ git clone https://github.com/DrSolidDevil/mlr-gd.git

$ cd mlr-gd

$ pip install .

```




To import the package into your script:  

```python

import melar

```







Example


```python

import numpy as np

import melar

# y = x1 + 0.5*x2

x = np.array([[1, 3, 5, 8], [1, 2, 3, 6]])

y = np.array([1.5, 4, 6.5, 11])

learning_rate = 0.01

generations = 100

model = melar.LinearRegression(weights_amount=2)

model.train(x, y, learning_rate, generations, do_print=True)

print(f"Weights: {model.weights}, Bias: {model.bias}")

```

```

Gen: 0, Cost: 95.4852602406095

Gen: 1, Cost: 5.593624864417041

Gen: 2, Cost: 0.3286224504551768

Gen: 3, Cost: 0.020244781001893267

...

Gen: 99, Cost: 0.0007438760098695897

Training Complete

Weights: [0.94643617 0.57630021], Bias: -0.003265101149422934

```