Consider the following code snippet using scikit-learn: sgd_regressor = SGDRegressor() param_dist = { 'loss': ['squared_loss', 'huber', 'epsilon_insensitive'], 'alpha': loguniform(1e-4, 1e0), 'penalty': ['l1', 'l2', 'elasticnet'], 'epsilon': loguniform(1e-4, 1e-1),} random_search = RandomizedSearchCV(sgd_regressor, param_distributions=param_dist, n_iter=10, cv=3, scoring='neg_mean_squared_error') random_search.fit(X, y) Assume all the necessary imports and X, y to be the training dataset. Which of the following statements about the given code are correct?

(A) Option figure from the original question paper

(C) Option figure from the original question paper

(D) Option figure from the original question paper

(B) Option figure from the original question paper

Machine Learning Practice · End Term · 24 Dec 2023 · September 2023 term · Set FDD1

Question 29: Consider the following code snippet using scikit-learn: …

Question 29

+3 marksOne or more correct options

Consider the following code snippet using scikit-learn:

python

1sgd_regressor = SGDRegressor()
2
3
4param_dist = { 'loss': ['squared_loss', 'huber', 'epsilon_insensitive'],
5    'alpha': loguniform(1e-4, 1e0),
6    'penalty': ['l1', 'l2', 'elasticnet'],
7    'epsilon': loguniform(1e-4, 1e-1),}
8
9
10random_search = RandomizedSearchCV(sgd_regressor,
11  param_distributions=param_dist, n_iter=10, cv=3,
12  scoring='neg_mean_squared_error')
13random_search.fit(X, y)

Assume all the necessary imports and $X, y$ to be the training dataset. Which of the following statements about the given code are correct?

Select all that apply.

Show answer

Correct answers

See the whole paper Take it as a mock test

Question 29 of 38 in the IIT Madras BS Machine Learning Practice (MLP) End Term paper sat on 24 Dec 2023, in the September 2023 term (IIT M DIPLOMA FN EXAM FDD1 24 Dec 2023). It carries 3 marks.

Question 29: Consider the following code snippet using scikit-learn: …

Question 29

More questions from this paper