Question 19
Go through the code snippet given below and answer the given subquestions.
import numpy as npfrom sklearn.linear_model import SGDRegressorfrom sklearn.pipeline import make_pipelinen_samples, n_features = 18, 4rng = np.random.RandomState(0)y = rng.randn(n_samples)X = rng.randn(n_samples, n_features)reg = SGDRegressor(max_iter=1000, tol=1e-3, eta0= 0.04, power_t=5, n_iter_no_change=3, validation_fraction=0.3 , random_state=42)reg.fit(X, y)print(reg.coef_)-0.528
1
0.528
Given code will return an error