Suppose you are using gradient descent to minimize the cost function in linear regression. During the gradient descent iterations, you observe that the cost function decreases, but the algorithm converges very slowly. What could be a possible solution to improve convergence?

Group of answer choices

Add more features to the dataset.

Randomly initialize the parameters.

Decrease the learning rate.

Increase the learning rate.