Question 1

In the context of machine learning, what is a diagnostic?

Select one:

• This refers to the process of measuring how well a learning algorithm does on a test set (data that the algorithm was not trained on).
• A test that you run to gain insight into what is/isn’t working with a learning algorithm.
• An application of machine learning to medical applications, with the goal of diagnosing patients’ conditions.
• A process by which we quickly try as many different ways to improve an algorithm as possible, so as to see what works.

Correct Answer is: Yes! A diagnostic is a test that you run to gain insight into what is/isn’t working with a learning algorithm, to gain guidance into improving its performance.

Question 2.

True/False? It is always true that the better an algorithm does on the training set, the better it will do on generalizing to new data.

Select one

• True
• False

Correct Answer: Actually, if a model overfits the training set, it may not generalize well to new data.

Question 3.

For a classification task; suppose you train three different models using three different neural network architectures. Which data do you use to evaluate the three models in order to choose the best one?

Select one:

• The cross validation set
• The test set
• All the data -- training, cross validation and test sets put together.
• The training set

Correct Answer is Use the cross validation set to calculate the cross validation error on all three models in order to compare which of the three models is best.