Machine Learning Multiple Choice Questions and Answers

1. A multiple regression model has

1. only one independent variable
2. more than one dependent variable
3. more than one independent variable
4. none of the above

2. Which statement is true about prediction problems?

1. The output attribute must be categorical.
2. The output attribute must be numeric.
3. The resultant model is designed to determine future outcomes.
4. The resultant model is designed to classify current behavior.

3. A measure of goodness of fit for the estimated regression equation is the

1. multiple coefficient of determination
2. mean square due to error
3. mean square due to regression
4. none of the above

4. A nearest neighbor approach is best used

1. with large-sized datasets.
2. when irrelevant attributes have been removed from the data.
3. when a generalized model of the data is desireable.
4. when an explanation of what has been found is of primary importance.

5. A regression model in which more than one independent variable is used to predict the dependent variable is called

1. a simple linear regression model
2. a multiple regression models
3. an independent model
4. none of the above

6. A term used to describe the case when the independent variables in a multiple regression model are correlated is

1. regression
2. correlation
3. multicollinearity
4. none of the above

7. Adding more basis functions in a linear model... (pick the most probably option)

1. Decreases model bias
2. Decreases estimation bias
3. Decreases variance
4. Doesnt affect bias and variance

8. Another name for an output attribute.

1. predictive variable
2. independent variable
3. estimated variable
4. dependent variable

9. Bootstrapping allows us to

1. choose the same training instance several times.
2. choose the same test set instance several times.
3. build models with alternative subsets of the training data several times.
4. test a model with alternative subsets of the test data several times.

10. Choose the options that are correct regarding machine learning (ML) and artificial intelligence (AI),(A) ML is an alternate way of programming intelligent machines.(B) ML and AI have very different goals.(C) ML is a set of techniques that turns a dataset into a software.(D) AI is a software that can emulate the human mind.

1. (A), (B), (D)
2. (A), (C), (D)
3. (B), (C), (D)
4. All are correct