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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. PCA is most useful for non linear type models.
2. Which of the following are the advantage/s of Decision Trees?
3. Which condition is used to influence a variable directly by all the others?
4. For k cross-validation, smaller k value implies less variance.
5. Which of the following is correct with respect to random forest?
6. What is Decision Tree?
7. Which of the following expression is true?
8. Which is conclusively produced by Hierarchical Clustering?
9. End Nodes are represented by __________
10. Point out the wrong statement.
11. How the bayesian network can be used to answer any query?
12. Which of the following is a categorical outcome?
13. Point out the wrong statement.
14. Which of the following is one of the largest boost subclass in boosting?
15. K-means clustering consists of a number of iterations and not deterministic.
16. How the compactness of the bayesian network can be described?
17. Decision Trees can be used for Classification Tasks.
18. Hierarchical clustering should be mainly used for exploration.
19. Which of the following function is used for k-means clustering?
20. Hierarchical clustering should be primarily used for exploration.
21. Decision Nodes are represented by ____________
22. Which of the following library is used for boosting generalized additive models?
23. Point out the wrong combination.
24. Which of the following is not a machine learning algorithm?
25. To which does the local structure is associated?

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