(Choose 2 answers)
Suppose you have a dataset with n = 10 features and m = 5000 examples. After training your logistic regression classifier with gradient descent, you find that it has underfit the training set and does not achieve desired performance on the training or cross validation sets. Which of the following might be promising step:to take? Check all that apply.
A. Use an SVM with a Gaussian Kernel.
B. Use a different optimization method since using gradient descent to train logistic regression might result a local minimum.
C. Create / add new polynomial features.
D. Reduce the number of examples in the training set.
El 30
