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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 correct order of working?
3. The principal components are equal to left singular values if you first scale the variables.
4. Which of the following is finally produced by Hierarchical Clustering?
5. Which of the following is a common error measure?
6. 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.
7. Which function is used for k-means clustering?
8. Which of the following can be used to create the most common graph types?
9. Predicting with trees evaluate _____________ within each group of data.
10. For k cross-validation, smaller k value implies less variance.
11. How the compactness of the bayesian network can be described?
12. Which is conclusively produced by Hierarchical Clustering?
13. Decision Tree is a display of an algorithm.
14. Chance Nodes are represented by __________
15. Which of the following method is used for trainControl resampling?
16. Which of the following is the valid component of the predictor?
17. K-means clustering consists of a number of iterations and not deterministic.
18. Which of the following trade-off occurs during prediction?
19. Point out the wrong statement.
20. Point out the wrong statement.
21. True positive means correctly rejected.
22. Decision Trees can be used for Classification Tasks.
23. Which of the following is required by K-means clustering?
24. Which of the following is correct use of cross validation?
25. End Nodes are represented by __________

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