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Q.1
In a transactional database, EVERY transaction includes a transaction identity number.
True
False
Q.2
Data Matrix, Document Data and Transaction Data are examples of which type of data set?
Record
Graph
Numerical
Ordered
Q.3
Zip codes and click counts are ____________.
Continuous Attributes
Dynamic Attributes
Discrete Attributes
High Class Attributes
Q.4
Association technique identifies attributes that occur frequently together in a given data set.
True
False
Q.5
In a k-NN algorithm, similarity of records is based on the closeness of a record to numerical predictors in the other records.
True
False
Q.6
Spam filtering for e-mails is an example of classification approach of data mining
True
False
Q.7
The effectiveness of a classification rule can be judged making a probability of misclassification errors and summarizing the results in a .
classification matrix
classification hierarchy
dendogram
classification algorithm
Q.8
The market share of a business would be considered a lagging measure in the cause-and- effect modeling of data mining.
True
False
Q.9
In association analysis, the antecedent and consequent are sets of items that do not have any items in common.
True
False
Q.10
The problem of finding hidden structure in unlabled data is
Supervised learning
Unsupervised learning
Reinforcement learning
Machine learning
Q.11
Task of inferring model from a labeled trained data is
Unsupervised learning
Reinforcement learning
Supervised learning
None
Q.12
Data mining helps to determine what kind of people buy what kind of products. This belongs to which field?
Cross Market Analysis
Target Marketing
Customer Profiling
Customer Requirements
Q.13
______ are used in retail sales to identify patterns that are frequently purchased together.
Classification
Regression
Association
Clustering
Q.14
A college professor wishes to reach a certain level of savings before her retirement. This is related to which data mining task?
Clustering
Regression
Association
Classification
Q.15
In the average linkage clustering, the distance between two clusters is defined as the average of distances between all pairs of objects, where each pair is made up of one object from each group.
True
False
Q.16
Data mining is
Actual discovery phase of knowledge of KDD
Stage of selecting right data in KDD
Transformation phase of data in KDD
All the above
Q.17
In cluster analysis, the objects within clusters should exhibit a high amount of dissimilarity.
True
False
Q.18
A grocery store retailer is trying to decide whether to put bread on sale. This is related to which data mining task?
Association
Outlier analysis
Summarization
Prediction
Q.19
___________ is a data-mining technique used for classifying a set of observations into predefined classes
Logistic regression
k-NN algorithm
Discriminant analysis
Linear regression
Q.20
Text database can be ___________
A. unstructured
B. semi-structured
C. well-structured
Both A and B
A, B, C
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