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Data warehouse and Data mining: Classification, Prediction and Clustering
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Data warehouse and Data mining: Classification, Prediction and Clustering
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25 Questions

1. Point out the wrong statement.
2. Which of the following is characteristic of best machine learning method?
3. Which of the following is finally produced by Hierarchical Clustering?
4. How the bayesian network can be used to answer any query?
5. Point out the wrong statement.
6. For k cross-validation, smaller k value implies less variance.
7. Which of the following are the advantage/s of Decision Trees?
8. To which does the local structure is associated?
9. Which of the following expression is true?
10. Which of the following is the valid component of the predictor?
11. The principal components are equal to left singular values if you first scale the variables.
12. Hierarchical clustering should be mainly used for exploration.
13. Which function is used for k-means clustering?
14. Which of the following clustering requires merging approach?
15. Which clustering technique requires a merging approach?
16. Which of the following is not a machine learning algorithm?
17. A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.
18. Which of the following is correct use of cross validation?
19. Which of the following library is used for boosting generalized additive models?
20. K-means is not deterministic and it also consists of number of iterations.
21. Backtesting is a key component of effective trading-system development.
22. Which is conclusively produced by Hierarchical Clustering?
23. Which of the following is one of the largest boost subclass in boosting?
24. PCA is most useful for non linear type models.
25. True positive means correctly rejected.

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