Machine Learning MCQ Questions and Answers for Practice

1. Regression trees are often used to model ........... data.

1. linear
2. nonlinear
3. categorical
4. symmetrical

2. Selecting data so as to assure that each class is properly represented in both the training and test set.

1. cross validation
2. stratification
3. verification
4. bootstrapping

3. Simple regression assumes a ........... relationship between the input attribute and output attribute.

1. linear
2. quadratic
3. reciprocal
4. inverse

4. Supervised learning and unsupervised clustering both require at least one

1. hidden attribute.
2. output attribute.
3. input attribute.
4. categorical attribute.

5. Supervised learning differs from unsupervised clustering in that supervised learning requires

1. at least one input attribute.
2. input attributes to be categorical.
3. at least one output attribute.
4. ouput attriubutes to be categorical.

6. Suppose your model is overfitting. Which of the following is NOT a valid way to try and reduce the overfitting?

1. Increase the amount of training data.
2. Improve the optimisation algorithm being used for error minimisation.
3. Decrease the model complexity.
4. Reduce the noise in the training data.

7. The adjusted multiple coefficient of determination accounts for

1. the number of dependent variables in the model
2. the number of independent variables in the model
3. unusually large predictors
4. none of the above

8. The average positive difference between computed and desired outcome values.

1. root mean squared error
2. mean squared error
3. mean absolute error
4. mean positive error

9. The average squared difference between classifier predicted output and actual output.

1. mean squared error
2. root mean squared error
3. mean absolute error
4. mean relative error

10. The correlation between the number of years an employee has worked for a company and the salary of the employee is 0.75. What can be said about employee salary and years worked?

1. There is no relationship between salary and years worked.
2. Individuals that have worked for the company the longest have higher salaries.
3. Individuals that have worked for the company the longest have lower salaries.
4. The majority of employees have been with the company a long time.

11. The correlation coefficient for two real-valued attributes is 0.85. What does this value tell you?

1. The attributes are not linearly related.
2. As the value of one attribute increases the value of the second attribute also increases.
3. As the value of one attribute decreases the value of the second attribute increases.
4. The attributes show a curvilinear relationship.

12. The leaf nodes of a model tree are

1. averages of numeric output attribute values.
2. nonlinear regression equations.
3. linear regression equations.
4. sums of numeric output attribute values.

13. The multiple coefficient of determination is computed by

1. dividing SSR by SST
2. dividing SST by SSR
3. dividing SST by SSE
4. none of the above

14. The process of forming general concept definitions from examples of concepts to be learned.

1. Deduction
2. abduction
3. induction
4. conjunction

15. The standard error is defined as the square root of this computation.

1. The sample variance divided by the total number of sample instances.
2. The population variance divided by the total number of sample instances.
3. The sample variance divided by the sample mean.
4. The population variance divided by the sample mean.