A simple tutorial on linear regression programming in python
It has three implementations,
- self-developed regression with cost function being MSE + weight-decay regularization;
- gradient descent
- stochastic gradient descent
- directly invocation of scikit-learn ridge regression function.
The example shows how to fit a line for 2D or a plane for 3D.