1. In the regression problem, Y is quantitative (e.g price, blood pressure).

Group of answer choices:

False

True

2. In the regression problem, Y takes values in a finite, unordered set (survived/died, digit 0-9, cancer class of tissue sample).

Group of answer choices:

True

False

3. Which of the following is not true for Unsupervised learning

Group of answer choices:

A. Difficult to know how well your are doing.

B. No outcome variable, just a set of predictors (features) measured on a set of samples.

C. Can be useful as a pre-processing step for supervised learning.

D. Validation can be done easily.

4. Prediction accuracy versus interpretability: Linear models are easy to interpret; thin-plate splines are not.

Group of answer choices:

True

False

5.

Parsimony versus black-box: We often prefer a simpler model involving fewer variables over a black-box predictor involving them all.

Group of answer choices:

True

False