ISYE 6501, Midterm 1 EXPECTED QUESTIONS WITH
VERIFIED ANSWERS
Question 1.
What do descriptive questions ask?
ANSWER
What happened? (e.g., which customers are most alike)
Question 2.
What do predictive questions ask?
ANSWER
What will happen? (e.g., what will Google's stock price be?)
Question 3.
What do prescriptive questions ask?
ANSWER
What action(s) would be best? (e.g., where to put traffic lights)
Question 4.
What is a model?
ANSWER
Real-life situation expressed as math.
Question 5.
What do classifiers help you do?
ANSWER
differentiate
,Question 6.
What is a soft classifier and when is it used?
ANSWER
In some cases, there won't be a line that separates all of the labeled examples. So we use a
classifier that minimizes the number of mistakes.
Question 7.
What does it mean when the classifier/decision boundary is almost parallel to the vertical x-axis?
ANSWER
The horizontal attribute is all that is needed.
Question 8.
What does it mean when the classifier/decision boundary is almost parallel to the horizontal y-axis?
ANSWER
The vertical attribute is all that is needed.
Question 9.
What is time-series data?
ANSWER
The same data recorded over time often recorded at equal intervals
Question 10.
What is quantitative data?
ANSWER
Number with a meaning: higher means more, lower means less (e.g., age, sales, temperature,
income)
Question 11.
What is categorical data?
ANSWER
Numbers w/o meaning (e.g., zip codes), non-numeric (e.g., hair color), binary data (e.g.,
male/female, yes/no, on/off)
,Question 12.
Which of these is time series data?
A. The average cost of a house in the United States every year since 1820
B. The height of each professional basketball player in the NBA at the start of the season
ANSWER
A
Question 13.
Which of these is structured data?
A. The contents of a person's Twitter feed
B. The amount of money in a person's bank account
ANSWER
B
Question 14.
What is structured data?
ANSWER
Data that can be stores in a structured way
Question 15.
What is unstructured data?
ANSWER
Data that is not easily described and stored (e.g., written text)
Question 16.
A survey of 25 people recorded each person's family size and type of car. Which of these is a data
point? A. The 14th person's family size and car type
B. The 14th person's family size
C.The car type of each person
ANSWER
A.
A data point is all the information about one observation
, Question 17.
The farther the wrongly classified point is from the line ___
ANSWER
The bigger the mistake we've made
Question 18.
The term including the margin gets larger so the importance of a large margin out weights avoiding
mistakes and classifying known data samples.
ANSWER
As lambda gets larger
Question 19.
That term also drops towards zero, so the importance of minimizing mistakes and classifying known
data points outweighs having a large margin.
ANSWER
As lambda drops towards zero
Question 20.
What can SVMs be used for
ANSWER
to find a classifier with maximum seperation or margin between the two sets of points?
Question 21.
When to use SVM?
ANSWER
If it's impossible to avoid classification errors, SVM can find a classifier that trades off reducing
errors and enlarging the margin.
VERIFIED ANSWERS
Question 1.
What do descriptive questions ask?
ANSWER
What happened? (e.g., which customers are most alike)
Question 2.
What do predictive questions ask?
ANSWER
What will happen? (e.g., what will Google's stock price be?)
Question 3.
What do prescriptive questions ask?
ANSWER
What action(s) would be best? (e.g., where to put traffic lights)
Question 4.
What is a model?
ANSWER
Real-life situation expressed as math.
Question 5.
What do classifiers help you do?
ANSWER
differentiate
,Question 6.
What is a soft classifier and when is it used?
ANSWER
In some cases, there won't be a line that separates all of the labeled examples. So we use a
classifier that minimizes the number of mistakes.
Question 7.
What does it mean when the classifier/decision boundary is almost parallel to the vertical x-axis?
ANSWER
The horizontal attribute is all that is needed.
Question 8.
What does it mean when the classifier/decision boundary is almost parallel to the horizontal y-axis?
ANSWER
The vertical attribute is all that is needed.
Question 9.
What is time-series data?
ANSWER
The same data recorded over time often recorded at equal intervals
Question 10.
What is quantitative data?
ANSWER
Number with a meaning: higher means more, lower means less (e.g., age, sales, temperature,
income)
Question 11.
What is categorical data?
ANSWER
Numbers w/o meaning (e.g., zip codes), non-numeric (e.g., hair color), binary data (e.g.,
male/female, yes/no, on/off)
,Question 12.
Which of these is time series data?
A. The average cost of a house in the United States every year since 1820
B. The height of each professional basketball player in the NBA at the start of the season
ANSWER
A
Question 13.
Which of these is structured data?
A. The contents of a person's Twitter feed
B. The amount of money in a person's bank account
ANSWER
B
Question 14.
What is structured data?
ANSWER
Data that can be stores in a structured way
Question 15.
What is unstructured data?
ANSWER
Data that is not easily described and stored (e.g., written text)
Question 16.
A survey of 25 people recorded each person's family size and type of car. Which of these is a data
point? A. The 14th person's family size and car type
B. The 14th person's family size
C.The car type of each person
ANSWER
A.
A data point is all the information about one observation
, Question 17.
The farther the wrongly classified point is from the line ___
ANSWER
The bigger the mistake we've made
Question 18.
The term including the margin gets larger so the importance of a large margin out weights avoiding
mistakes and classifying known data samples.
ANSWER
As lambda gets larger
Question 19.
That term also drops towards zero, so the importance of minimizing mistakes and classifying known
data points outweighs having a large margin.
ANSWER
As lambda drops towards zero
Question 20.
What can SVMs be used for
ANSWER
to find a classifier with maximum seperation or margin between the two sets of points?
Question 21.
When to use SVM?
ANSWER
If it's impossible to avoid classification errors, SVM can find a classifier that trades off reducing
errors and enlarging the margin.
