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Problem 3: Now we will use the methods of ridge regression and lasso to solve our models. 1. The ridge regression cost function we will use is of the form $$L(X, y, \alpha, s) = \frac{1}{n}||Xa - y||_2^2 + s||\alpha||_2^2$$ We can solve the normal equations directly to obtain our model parameters using $$\alpha = (X^TX + (s/n)I)^{-1}X^Ty$$ Write a python function `ridge(X, y, s)` which returns the model parameters as a numpy array.

Name: problem 3 now we will use the methods of ridge regression and lasso to solve our models 1 the ridge regression cost function we will use is of the form lx y alpha s frac1nxa y22 salpha22 w 71526
Uploaded: 2023-09-29T17:27:06-08:00
Duration: 1 min 2 s
Channel: Sri K
Description: problem 3 now we will use the methods of ridge regression and lasso to solve our models 1 the ridge regression cost function we will use is of the form lx y alpha s frac1nxa y22 salpha22 w 71526

          Problem 3:
Now we will use the methods of ridge regression and lasso to solve our models.
1. The ridge regression cost function we will use is of the form
$$L(X, y, \alpha, s) = \frac{1}{n}||Xa - y||_2^2 + s||\alpha||_2^2$$
We can solve the normal equations directly to obtain our model parameters using
$$\alpha = (X^TX + (s/n)I)^{-1}X^Ty$$
Write a python function `ridge(X, y, s)` which returns the model parameters as a numpy array.

$problem 3 now we will use the methods of ridge regression and lasso to solve our models 1 the ridge regression cost function we will use is of the form lx y alpha s frac1nxa y22 salpha22 w 71526$

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