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Machine Learning (Introduction)

Total questions: 10

Worksheet time: 50mins

Name
Class
Date
1.

Which model is the best choice for fraud detection?

a)

Precision = 0.8, Recall = 0.4

b)

Precision = 0.4, Recall = 0.8

c)

Precision = 0.7, Recall = 0.7

2.

For the application of telesales, suppose we have a million customers in database, a company want to make a phone call for offering special privileges to customers who are likely to purchase. Calling to all of them is impossible. Which measures are the most important to identify possible customers?

a)

Precision

b)

Recall

c)

Sensitivity

d)

Specificity

3.

What is the concept of reinforcement learning?

a)

Learning from labeled data

b)

Learning from unlabeled data

c)

Learning from environment

4.

Why do we need to set hyper-parameters?

a)

Model configuration

b)

Model validation

c)

Model deployment

5.

What is the correct for the red dot for the application of diabetes prediction?

a)

Setting threshold = 0, All samples have diabetes

b)

Setting threshold = 1, All samples do not have diabetes

c)

Setting threshold = 0, All samples do not have diabetes

d)

Setting threshold = 1, All samples have diabetes

6.

What is the correct for the red dot for the application of diabetes prediction?

a)

Setting threshold = 0, All samples have diabetes

b)

Setting threshold = 1, All samples do not have diabetes

c)

Setting threshold = 0, All samples do not have diabetes

d)

Setting threshold = 1, All samples have diabetes

7.

What is True (You may have multiple answer)

a)

Training accuracy = 0.90, Testing accuracy = 0.89, your model is good enough to deploy for diabetes prediction

b)

Area under curve of ROC is 0.9, your model is good enough to deploy for lung cancer prediction

c)

Training accuracy = 0.90, Testing accuracy = 0.89, your model is not overfit

d)

Area under curve of PR Curve is 0.9, your model is good enough to deploy for lung cancer prediction

8.

Which model is good enough for fraud detection?

a)

Precision = 0.9, Recall = 0.9

b)

Precision = 0.9, Recall = 0.6

c)

Precision = 0.6, Recall = 0.9

d)

Precision = 0.6, Recall = 0.6

9.

What is limitation of over sampling?

a)

It could make model underfit

b)

It could make model overfit

10.

What is limitation of under sampling

a)

It could make model underfit

b)

It could make model overfit