Machine Learning MCQ Multiple Choice Questions Answers | Quiz for Practice
MCQ quiz on Machine Learning multiple choice questions and answers on Machine Learning MCQ questions on Machine Learning objectives questions with answer test pdf for interview preparations, freshers jobs and competitive exams.
Machine Learning MCQ Questions for Practice
1. Regression trees are often used to model ........... data.
Correct Answer is: symmetrical
2. Selecting data so as to assure that each class is properly represented in both the training and test set.
Correct Answer is: bootstrapping
3. Simple regression assumes a ........... relationship between the input attribute and output attribute.
Correct Answer is: inverse
4. Supervised learning and unsupervised clustering both require at least one
Correct Answer is: categorical attribute.
5. Supervised learning differs from unsupervised clustering in that supervised learning requires
Correct Answer is: 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?
Correct Answer is: Reduce the noise in the training data.
7. The adjusted multiple coefficient of determination accounts for
Correct Answer is: unusually large predictors
8. The average positive difference between computed and desired outcome values.
Correct Answer is: mean absolute error
9. The average squared difference between classifier predicted output and actual output.
Correct Answer is: 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?
Correct Answer is: 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?
Correct Answer is: The attributes show a curvilinear relationship.
12. The leaf nodes of a model tree are
Correct Answer is: sums of numeric output attribute values.
13. The multiple coefficient of determination is computed by
Correct Answer is: none of the above
14. The process of forming general concept definitions from examples of concepts to be learned.
Correct Answer is: conjunction
15. The standard error is defined as the square root of this computation.
Correct Answer is: The population variance divided by the sample mean.
16. This clustering algorithm initially assumes that each data instance represents a single cluster.
Correct Answer is: expectation maximization
17. This clustering algorithm merges and splits nodes to help modify nonoptimal partitions.
Correct Answer is: conceptual clustering
18. This supervised learning technique can process both numeric and categorical input attributes.
Correct Answer is: backpropagation learning
19. This technique associates a conditional probability value with each data instance.
Correct Answer is: multiple linear regression
20. This unsupervised clustering algorithm terminates when mean values computed for the current iteration of the algorithm are identical to the computed mean values for the previous iteration.
Correct Answer is: expectation maximization
21. When doing least-squares regression with regularisation (assuming that the optimisation can be done exactly), increasing the value of the regularisation parameter (Lambda)
Correct Answer is: will never increase the testing error.
22. Which is not true about Gradient of a continuous and differentiable function
Correct Answer is: decreases as you get closer to the minimum
23. Which of the following is a common use of unsupervised clustering?
Correct Answer is: determine if meaningful relationships can be found in a dataset
24. Which of the following is not an advantage of Grid search
Correct Answer is: It is easy to implement.
25. Which of the following points would Bayesians and frequentists disagree on?
Correct Answer is: The use of class priors in Gaussian Discriminant Analysis
26. Which of the following sentence is FALSE regarding regression?
Correct Answer is: It may be used for interpretation.
27. Which statement about outliers is true?
Correct Answer is: Outliers should be part of the test dataset but should not be present in the training data.
28. Which statement is true about neural network and linear regression models?
Correct Answer is: Both techniques build models whose output is determined by a linear sum of weighted input attribute values.
29. Which statement is true about prediction problems?
Correct Answer is: The resultant model is designed to determine future outcomes.
