What do we do if we want to see if algorithms' performances differ?

- Look up the Z-score in Normal distribution tables
- Look up the Z-score in one-tailed tables
Look up the Z-score in two-tailed tables

- Look up the Z-score in binomial tables

What assumption underlies a null hypothesis test?

- that the algorithms don't work
- that the algorithms return a null result
that there is no performance difference between algorithms

- that the algorithms differ in performance

What is `ground truth'?

data known to be correct

- the true values obtained by an algorithm
- images of the ground
- values obtained by an algorithm that are known to be true

What are the axes of a ROC curve?

- TP and FN
- TP and TN
- FP and FN
TP and FP

Which corner of a ROC curve indicates the best performance?

- upper left
- upper right
upper left

- lower right

You are developing software for the Police to show mugshots of suspects to the witness of a crime. Which of the following is the best approach to take?

- maximize the number of true positives
- minimize the number of false positives
- minimize the number of false negatives
maximize the number of true positives, even if the false positive rate is high

What is a false positive?

- A positive result that is false
A true result from an algorithm that is incorrect

- A false result from an algorithm that should be correct
- A false result from an algorithm

You are developing a automatic passport system for use by immigration, where pictures of people are compared to those in their passports. Which of the following is the best approach to take?

- maximize the number of true positives
minimize the number of false positives

- minimize the number of false negatives
- maximize the number of true positives, even if the false positive rate is high

When evaluating vision systems, it is normal to:

have different training and test sets

- train on the training set and test using both training and test sets
- train on all data but test on only the test set
- use the same training and test sets

What is a false negative?

- A false result from an algorithm
A false result from an algorithm that should have succeeded

- A negative result that is false
- A false result from an algorithm that should be negative