11. The SVM's are less effective when:
12. The process of forming general concept definitions from examples of concepts to be learned.
13. What is 'Test set'?
14. Regarding bias and variance, which of the following statements are true? (Here 'high' and 'low' are relative to the ideal model. (i) Models which overfit are more likely to have high bias (ii) Models which overfit are more likely to have low bias (iii) Models which overfit are more likely to have high variance (iv) Models which overfit are more likely to have low variance
15. Selecting data so as to assure that each class is properly represented in both the training and test set.
16. Which of the following scale data by removing elements that don't belong to a given range or by considering a maximum absolute value.
17. Which of the following selects the best K high-score features.
18. Which of the following statements are true for a design matrix X ∈ Rn×d with d > n? (The rows are n sample points and the columns represent d features.)
19. Attribute selection measures are also known as splitting rules.
20. . . . . . . . . produce sparse matrices of real numbers that can be fed into any machine learning model.
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