Reference no: EM132418222

True / False Questions

1. Correlations, trends, clusters, trajectories, and anomalies are examples for derived patterns of Predictive Data Mining Tasks

2. There are two types of predictive modeling tasks: Classification and Regression.

3. Regression is used for discrete target variables, and Classification is used for continuous target variables.

4. Association analysis is used to discover patterns that describe strongly associated features in the data.

5. The three most common examples of Minkowski distances are: Hamming distance, Euclidean distance, and Supremum distance.

6. Simple Matching Coefficient (SMC) and Jaccard Coefficient are examples of similarity and dissimilarity measures.

7. The cosine similarity is one of the most common measures of document similarity

8. If the correlation is < 0, then there is no linear relationship between the two sets of values

9. A classification model is an abstract representation of the relationship between the attribute set and the class label.

10. Cluster Analysis model can be represented as a tree, a probability table, or a vector of real-valued parameters.

11. In Classification, there are no restrictions on the type of attributes that can be used as predictor variables.

12. In Regression, the class label, must be of nominal type.

13. Binary classifiers assign each data instance to one of two possible labels, typically denoted as +1 and -1.

14. A probabilistic classifier produces a discrete-valued label to each data instance it classifies.

15. A nonlinear classifier enables the construction of a complex, nonlinear decision surfaces.

16. A global classifier partitions the input space into smaller regions and fits a distinct model to training instances in each region.

17. Association analysis used for discovering interesting relationships hidden in large data sets.

18. The strength of an association rule can be measured in terms of its support and confidence.

19. In Association analysis, a rule that has very low Confidence

• Might occur simply by chance.
• Unlikely to be interesting because it might not be profitable to promote items that customers seldom buy together

20. In Association analysis, Support measures the reliability of the inference made by a rule.

21. If sequence s = ?{2,4}{3,5,6}{8}? and sequence t= ?{2}{3,6}{8}? then t is a subsequence of s

22. If sequence s = ?{1,2}{3,4}? and sequence t = ?{1}{2}? then t is a subsequence of s

23. the three phases of the Apriori algorithm for frequent itemset discovery are: Candidate Generation, Candidate Pruning, and Support Counting.

24. The "maxspan constraint" specifies the maximum allowed time difference between the latest and the earliest occurrences of events in the entire sequence.

25. Co-clustering automatically provides a description of a cluster of objects in terms of attributes