ISYE 6501 | FINAL EXAM | ACTUAL QUESTIONS AND
CORRECT ANSWERS | LATEST UPDATE | GRADED A+ |
SAVE TIME AND ANXIETY | ACE IN THE ISYE FINALS |
100% ACCURATE
185 Minute Time Limit
Instructions
Work alone. Do not collaborate with or copy from anyone else.
You may use any of the following resources:
o Two sheets (both sides) of handwritten (not photocopied, scanned, or printed)
notes
If any question seems ambiguous, use the most reasonable interpretation
(i.e., don't be like Calvin):
Instructions for Questions 1–8
For each of the following eight questions, select the type of problem that the model is best
suited for. Each type of problem might be used zero, one, or more than one time in the eight
questions.
,
,Question 3:
Select the type of problem that k-means is best suited for.
A. Classification
B. Clustering
C. Experimental design
D. Prediction from feature data
E. Prediction from time-series data
F. Variable selection
Correct Answer: B. Clustering
Explanation:
K-means is an unsupervised learning algorithm used to group data points into clusters based on
similarity. It is not used for classification or prediction tasks, but rather for identifying natural
groupings within a dataset.
Question 4:
Select the type of problem that GARCH is best suited for.
A. Classification and/or prediction from feature data
B. Clustering
C. Experimental design
D. Prediction from time-series data
E. Variable selection
Correct Answer: D. Prediction from time-series data
Explanation:
GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models are designed to
analyze and forecast time-series data, particularly for modeling volatility in financial or
economic datasets. They are not suitable for clustering, experimental design, or standard
classification tasks.
,
CORRECT ANSWERS | LATEST UPDATE | GRADED A+ |
SAVE TIME AND ANXIETY | ACE IN THE ISYE FINALS |
100% ACCURATE
185 Minute Time Limit
Instructions
Work alone. Do not collaborate with or copy from anyone else.
You may use any of the following resources:
o Two sheets (both sides) of handwritten (not photocopied, scanned, or printed)
notes
If any question seems ambiguous, use the most reasonable interpretation
(i.e., don't be like Calvin):
Instructions for Questions 1–8
For each of the following eight questions, select the type of problem that the model is best
suited for. Each type of problem might be used zero, one, or more than one time in the eight
questions.
,
,Question 3:
Select the type of problem that k-means is best suited for.
A. Classification
B. Clustering
C. Experimental design
D. Prediction from feature data
E. Prediction from time-series data
F. Variable selection
Correct Answer: B. Clustering
Explanation:
K-means is an unsupervised learning algorithm used to group data points into clusters based on
similarity. It is not used for classification or prediction tasks, but rather for identifying natural
groupings within a dataset.
Question 4:
Select the type of problem that GARCH is best suited for.
A. Classification and/or prediction from feature data
B. Clustering
C. Experimental design
D. Prediction from time-series data
E. Variable selection
Correct Answer: D. Prediction from time-series data
Explanation:
GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models are designed to
analyze and forecast time-series data, particularly for modeling volatility in financial or
economic datasets. They are not suitable for clustering, experimental design, or standard
classification tasks.
,
