Revision Sheet.pdf

Revision Sheet 1. Any facts, numbers, or text that can be processed by a computer. a. Data b. Information c. Knowledge d. None of the above 2. ____________is the awareness of data brought into relation to form information in a wider sense. a. Knowledge. b. Da...

Revision Sheet 1. Any facts, numbers, or text that can be processed by a computer. a. Data b. Information c. Knowledge d. None of the above 2. ____________is the awareness of data brought into relation to form information in a wider sense. a. Knowledge. b. Data. c. Information. d. None of the above 3. ________ databases are owned by particular departments or business groups such as sales, cost. a. Operational b. Informational c. Both informational and operational. d. Flat. 4. ……… to transform data into appropriate form for data mining a. Data cleaning b. Data integration c. Data selection d. Data transformation 5. …….. to retrieve relevant data for analysis a. Data cleaning b. Data integration c. Data selection d. Data transformation 6. ………….. is the search for relationships and global patterns that exist in large databases. a. Machine learning b. Artificial Intelligence c. Data Mining d. Interpolation Search 7. KDD stands for ________. a. Knowledge database. b. Knowledge discovery in database. c. Knowledge data house. d. Knowledge data definition 8. Removing duplicate records is a process called _____________. a. Data Mining b. Pattern evaluation c. Knowledge presentation d. Data cleaning 9. Which of the following is not the concept of a data warehouse? a. a collection of data created to support decision-making applications. b. process of data extraction, transformation, and loading of data to the warehouse. c. normally used for models and forecasting. d. access of the data by end-users and applications. 10. Data integration process aimed to ….. a. combine multiple sources b. retrieve relevant data for analysis c. transform data into appropriate form for data mining d. identify the truly interesting patterns representing knowledge based on interestingness measures. 11. ……………….. is a single, complete and consistent store of data obtained from a variety of different sources. a. Database b. Data Warehouse c. Data Store d. None of the above 12. Which of the following kinds of data? a. Data warehouse. b. Relational database. c. Advanced database and information repository. d. All of the above. 13. ………………. is a simple statement of truth. a. Fact b. Concept c. Procedure d. Principle 14. the outputs from a data mining session are ______. a. Facts. b. Concepts. c. Procedures. d. Principles. 15. ___________is step-by-step action to achieve a goal. a. Fact. b. Concept. c. Procedure. d. Principle. 16. ………..... are general truths or laws that are basic to other truths. a. Facts b. Concepts c. Procedures d. Principles 23. A data mining method that builds models from data without predefined classes. a. Supervised Learning b. Unsupervised Learning c. Semi-supervised learning d. Reinforcement learning 24. Finds natural grouping of instances given unlabeled data a) Clustering b) Classification c) Regression d) Association Rules 25. ………...a form of data analysis that extracts models describing important data classes. a. Classification b. Analysis of data c. Extraction of data d. Dataset 26. In ________ the groups are not predefined. a. Association rules. b. Summarization. c. Clustering. d. Prediction 27. Which of the following is finally produced by Hierarchical Clustering? a) final estimate of cluster centroids b) tree showing how close things are to each other c) assignment of each point to clusters d) all of the mentioned 28. Hierarchical clustering should be primarily used for exploration. a) True b) False 29. …………. method works by grouping data objects into a hierarchy or “tree” of the cluster. a. Hierarchical b. K-Means c. K-Medoids d. None of the above 30. There are …… styles of hierarchical clustering algorithms to build a tree from the input set S a. 1 b. 2 c. 3 d. 4 31. Agglomerative is ……. tree a. Top-Down b. Bottom-Up c. Both a & b d. None of the above 32. Divisive is ……. Tree a. Top-Down b. Bottom-Up c. Both a & b d. None of the above 33. Consider the distance between one cluster and another cluster to be equal to the shortest distance from any member of one cluster to any member of the other cluster. a. Single linkage b. Complete linkage c. Average linkage d. None of the above 34. A general version of K-means………. a. Hierarchical b. K-Means c. K-Medoids d. None of the above 35. The …… method can be integrated to cluster data with mixed numeric and nominal values. a. Hierarchical b. K-Means c. K-Medoids d. None of the above 36. k-medoids is a: a. Partitioning methods b. Hierarchical Methods c. Model-based clustering d. None of the above 37. which of the following is not a clustering Method: a. K-means b. CLARANS c. k-medoids d. None of the above 38. ___________ is a self-learning technique in which system has to explore data. a. Supervised Learning b. Unsupervised Learning c. semi-supervised Learning d. Reinforcement Learning 39. Given P1(3,4), P2(2,6), P3(3,8), P4(4,7), P5(7,4), P6(6,2), P7(6,4), P8(7,3), P9(8,5), P10(7,6). Assuming P1 and P5 are selected as medoids. The total cost is …….. a. 10 b. 20 c. 30 d. 40 40. In the figure below, if you draw a horizontal line on y-axis for y=2. What will be the number of clusters formed? a. 1 b. 2 c. 3 d. 4 41. What is the appropriate no. of clusters for the following dendrogram? a. 2 b. 4 c. 6 d. 8 42. From which library we import Agglomerative Clustering class? a. Matplotlib b. Pandas c. Sklearn d. Numpy 43. The linkage method in the below code performs: cluster = AgglomerativeClustering(n_clusters=5, affinity='euclidean', linkage='single') a. max/farthest point linkage on the distance matrix. b. min/nearest linkage on the distance matrix c. average linkage on the distance matrix. d. weighted linkage on the distance matrix. 44. The linkage method in the below code performs: cluster = AgglomerativeClustering(n_clusters=5, affinity='euclidean', linkage='complete') a. max/farthest point linkage on the distance matrix. b. min/nearest linkage on the distance matrix c. average linkage on the distance matrix. d. weighted linkage on the distance matrix. 45. What is the form of Fuzzy logic? a) Two-valued logic. b) Crisp set logic. c) Many-valued logic. d) Binary set logic. 46. Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. a) AND. b) OR. c) NOT. d) All of the above. 47. Fuzzy logic is usually represented as ___________. a) IF-THEN-ELSE rules. b) IF-THEN rules. c) Both IF-THEN-ELSE rules & IF-THEN rules. d) None of the above 48. Fuzzy Logic can be implemented in? a) Hardware. b) Software. c) Both A and B. d) None of the Above. 49. Each element of X is mapped to a value between 0 and 1. It is called _____. a) membership value. b) degree of membership. c) Boolean logic. d) Both A and B. 50. The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______. a) Fuzzy Set. b) Crisp Set. c) Both A and B. d) None of the Above. 51. __________ is defined in such a way as to the individuals in some given universe of discourse into two groups. a. Fuzzy set. b. Crisp set. c. Fuzzy Logic. d. None. 52. __________ is defined mathematically by assigning to each possible individual in the universe of discourse a value representing its grade of membership. a. Fuzzy Logic. b. Crisp set. c. Fuzzy set. d. None. 53. __________ is a curve that define show each point in the input space. a. Fuzzy logic (FL). b. Membership Function (MF). c. Fuzzy set. 54. _______ is a way of mapping an input space to an output space using fuzzy logic. a. Membership Function (MF). b. Fuzzy logic (FL). c. Fuzzy Inference System (FIS). 55. The first step in fuzzy logic processing called _________. a. Fuzzification. b. Rule valuation. c. Defuzzification. d. Aggregation of all outputs. 56. Which of the following steps use center of gravity (COG) and maximum methods? a. Fuzzification. b. Rule valuation. c. Defuzzification. d. Aggregation of all outputs. 57. ____________ are usually if-then statements. a. Fuzzification. b. Fuzzy Rules. c. Defuzzification. d. None of the above. 58. Traditional set theory is also known as Crisp Set theory. a) True b) False 59. Given, distance matrix of 5 points: 1,2 1- How many clusters are there initially (before any fusions have happened)? a. None b. 1 c. 4 d. 5 2- Based on the concept of agglomerative clustering, which two points will get clustered first? a. A,B b. B,C c. C,D d. D,E 3- Which clusters will be fused in step two? a. C with (A,B) b. D with (A,B) c. C,D d. C,E 60. data set of 5 objects as follows: Initialize number of clusters k = 2 assume X3 (4,6) and X4 (6,7) are selected as medoids Using the Manhattan distance, what are the instances for each cluster? a. Cluster1(X3, X5, X1) and Cluster2 (X4, X2) b. Cluster1(X3, X1) and Cluster2 (X4, X2, X5) c. Cluster1(X3, X1, X2) and Cluster2 (X4, X5) d. Cluster1(X3, X1) and Cluster2 (X4, X2, X5) 61. According to your results, calculate the total cost: a. 3 b. 4 c. 5 d. 2