Lets start coding for linear regression
As from previous post, linear regression has analytical solution. For a given dataset the optimization problem reduces to linear algebra psudeo-inverse problem.
``` W = (XX')^-1XY```
This would be the training step for the algorithm. Python code would be very easy.
np.linalg.inv(X.dot(X.T)).dot(X).dot(Y)
Later once the parameters W is defined runtime would be a single matrix multiplication as our linear model.
Y' = WX
Could be written as
Y_est = W.dot(X)
Comments
Post a Comment