ISYE 6501 — Introduction to Analytics Modeling
Final Exam — 100 Questions
Georgia Institute of Technology
Instructions: For each question, select the answer that best fits the
Total Points: 50 pts (0.5 pts each)
question.
■ Red highlight = Correct answer ■ Radio button = Your selection area
Question 1 0..5 pts
Select the type of problem that linear regression is best suited for.
■ Classification
■ Clustering
■ Experimental design
● Prediction from feature data
■ Prediction from time-series data
■ Variable selection
Question 2 0..5 pts
Select the type of problem that logistic regression is best suited for.
● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 3 0..5 pts
Select the type of problem that lasso regression is best suited for.
■ Classification
■ Clustering
■ Experimental design
■ Prediction from time-series data
● Variable selection and/or prediction from feature data
,Question 4 0..5 pts
Select the type of problem that ridge regression is best suited for.
■ Classification
■ Clustering
■ Experimental design
● Prediction from feature data
■ Prediction from time-series data
■ Variable selection
Question 5 0..5 pts
Select the type of problem that elastic net is best suited for.
■ Classification
■ Clustering
■ Experimental design
● Variable selection and/or prediction from feature data
■ Prediction from time-series data
Question 6 0..5 pts
Select the type of problem that k-means clustering is best suited for.
■ Classification
● Clustering
■ Experimental design
■ Prediction from feature data
■ Prediction from time-series data
Question 7 0..5 pts
Select the type of problem that k-nearest neighbors (KNN) is best suited for.
, ● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 8 0..5 pts
Select the type of problem that support vector machine (SVM) is best suited for.
● Classification
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 9 0..5 pts
Select the type of problem that random forest is best suited for.
● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 10 0..5 pts
Select the type of problem that decision tree is best suited for.
● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 11 0..5 pts
Final Exam — 100 Questions
Georgia Institute of Technology
Instructions: For each question, select the answer that best fits the
Total Points: 50 pts (0.5 pts each)
question.
■ Red highlight = Correct answer ■ Radio button = Your selection area
Question 1 0..5 pts
Select the type of problem that linear regression is best suited for.
■ Classification
■ Clustering
■ Experimental design
● Prediction from feature data
■ Prediction from time-series data
■ Variable selection
Question 2 0..5 pts
Select the type of problem that logistic regression is best suited for.
● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 3 0..5 pts
Select the type of problem that lasso regression is best suited for.
■ Classification
■ Clustering
■ Experimental design
■ Prediction from time-series data
● Variable selection and/or prediction from feature data
,Question 4 0..5 pts
Select the type of problem that ridge regression is best suited for.
■ Classification
■ Clustering
■ Experimental design
● Prediction from feature data
■ Prediction from time-series data
■ Variable selection
Question 5 0..5 pts
Select the type of problem that elastic net is best suited for.
■ Classification
■ Clustering
■ Experimental design
● Variable selection and/or prediction from feature data
■ Prediction from time-series data
Question 6 0..5 pts
Select the type of problem that k-means clustering is best suited for.
■ Classification
● Clustering
■ Experimental design
■ Prediction from feature data
■ Prediction from time-series data
Question 7 0..5 pts
Select the type of problem that k-nearest neighbors (KNN) is best suited for.
, ● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 8 0..5 pts
Select the type of problem that support vector machine (SVM) is best suited for.
● Classification
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 9 0..5 pts
Select the type of problem that random forest is best suited for.
● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 10 0..5 pts
Select the type of problem that decision tree is best suited for.
● Classification and/or prediction from feature data
■ Clustering
■ Experimental design
■ Prediction from time-series data
■ Variable selection
Question 11 0..5 pts
