DSCI 4330 Exam 2 | UPDATED Questions with 100%
Verified Answers
Q1: All of the following statements about data mining are true
except
A. the valid aspect means that the discovered patterns should
hold true on new data
B. the potentially useful aspect means that the results should
lead to some business benefit
C. the process aspect means that data mining should be a
one-step process to results
D. the novel aspect means that previously unknown patterns
are discovered
A: C. the process aspect means that data mining should be a one-step process to results
Q2: "The nontrivial process of identifying valid, novel, potentially
useful, and ultimately understandable patterns in data stored
in structured databases." is a definition for ...
A. Data warehousing
B. Data wrangling
C. Data mining
D. ETL
A: C. Data mining
Q3: Which broad area of data mining applications analyzes data,
forming rules to distinguish between defined classes?
A. classification
B. visualization
C. associations
D. clustering
A: A. classification
Q4: Clustering partitions a collection of things into segments
whose members share
A. similar collection methods.
B. dissimilar characteristics.
C. similar characteristics.
D. dissimilar collection methods.
A: C. similar characteristics
Q5: Data mining can be very useful in detecting patterns such as
credit card fraud, but is of little help in improving sales.
True
False
, A: False
Q6: Ensemble models for predictive analytics produce more
robust and reliable predictions.
True
False
A: True
Q7: What is the most popular data mining process in the industry?
A. KDD Process
B. SEMMA
C. CRISP-DM
A: C. CRISP-DM
Q8: Market Basket Analysis is an example of
A. Cluster analysis
B. Regression analysis
C. Association analysis
D. Classification analysis
A: C. Association analysis
Q9: Data mining is only for large firms that have lots of customer
data.
True
False
A: False
Q10: Which broad area of data mining applications partitions a
collection of objects into natural groupings with similar
features?
A. clustering
B. regression
C. visualization
D. associations
A: A. clustering
Q11: What data mining technique can be used to improve product
placement on the sales floor by revealing the patterns of
combinations of retail products purchased together?
A. Linear regression analysis of products
B. Cluster analysis of products
C. Association rule mining
D. Classification of products
A: C. Association rule mining
Verified Answers
Q1: All of the following statements about data mining are true
except
A. the valid aspect means that the discovered patterns should
hold true on new data
B. the potentially useful aspect means that the results should
lead to some business benefit
C. the process aspect means that data mining should be a
one-step process to results
D. the novel aspect means that previously unknown patterns
are discovered
A: C. the process aspect means that data mining should be a one-step process to results
Q2: "The nontrivial process of identifying valid, novel, potentially
useful, and ultimately understandable patterns in data stored
in structured databases." is a definition for ...
A. Data warehousing
B. Data wrangling
C. Data mining
D. ETL
A: C. Data mining
Q3: Which broad area of data mining applications analyzes data,
forming rules to distinguish between defined classes?
A. classification
B. visualization
C. associations
D. clustering
A: A. classification
Q4: Clustering partitions a collection of things into segments
whose members share
A. similar collection methods.
B. dissimilar characteristics.
C. similar characteristics.
D. dissimilar collection methods.
A: C. similar characteristics
Q5: Data mining can be very useful in detecting patterns such as
credit card fraud, but is of little help in improving sales.
True
False
, A: False
Q6: Ensemble models for predictive analytics produce more
robust and reliable predictions.
True
False
A: True
Q7: What is the most popular data mining process in the industry?
A. KDD Process
B. SEMMA
C. CRISP-DM
A: C. CRISP-DM
Q8: Market Basket Analysis is an example of
A. Cluster analysis
B. Regression analysis
C. Association analysis
D. Classification analysis
A: C. Association analysis
Q9: Data mining is only for large firms that have lots of customer
data.
True
False
A: False
Q10: Which broad area of data mining applications partitions a
collection of objects into natural groupings with similar
features?
A. clustering
B. regression
C. visualization
D. associations
A: A. clustering
Q11: What data mining technique can be used to improve product
placement on the sales floor by revealing the patterns of
combinations of retail products purchased together?
A. Linear regression analysis of products
B. Cluster analysis of products
C. Association rule mining
D. Classification of products
A: C. Association rule mining
