ISYE 6501 FINAL EXAM STUDY GUIDE
WITH BEST SOLUTIONS
Why is it important to scale our data when using SVM? -
answer-We're looking to minimize the sum of the squares of
the coefficients, but if our data has very different scales a
small change in one could swamp a huge change in the
other.
what does it signify when a coefficient for a classifier is
close to zero - answer-it means the corresponding attribute
is probably not relevant
What do descriptive questions ask? - answer-What
happened? (e.g., which customers are most alike)
What do predictive questions ask? - answer-What will
happen? (e.g., what will Google's stock price be?)
What do prescriptive questions ask? - answer-What
action(s) would be best? (e.g., where to put traffic lights)
,What is a model? - answer-Real-life situation expressed as
math.
What do classifiers help you do? - answer-differentiate
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.
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.
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.
What is time-series data? - answer-The same data recorded
over time often recorded at equal intervals
,What is quantitative data? - answer-Number with a
meaning: higher means more, lower means less (e.g., age,
sales, temperature, income)
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)
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
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
What is structured data? - answer-Data that can be stores
in a structured way
, What is unstructured data? - answer-Data that is not easily
described and stored (e.g., written text)
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
The farther the wrongly classified point is from the line ___
- answer-The bigger the mistake we've made
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
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
WITH BEST SOLUTIONS
Why is it important to scale our data when using SVM? -
answer-We're looking to minimize the sum of the squares of
the coefficients, but if our data has very different scales a
small change in one could swamp a huge change in the
other.
what does it signify when a coefficient for a classifier is
close to zero - answer-it means the corresponding attribute
is probably not relevant
What do descriptive questions ask? - answer-What
happened? (e.g., which customers are most alike)
What do predictive questions ask? - answer-What will
happen? (e.g., what will Google's stock price be?)
What do prescriptive questions ask? - answer-What
action(s) would be best? (e.g., where to put traffic lights)
,What is a model? - answer-Real-life situation expressed as
math.
What do classifiers help you do? - answer-differentiate
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.
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.
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.
What is time-series data? - answer-The same data recorded
over time often recorded at equal intervals
,What is quantitative data? - answer-Number with a
meaning: higher means more, lower means less (e.g., age,
sales, temperature, income)
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)
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
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
What is structured data? - answer-Data that can be stores
in a structured way
, What is unstructured data? - answer-Data that is not easily
described and stored (e.g., written text)
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
The farther the wrongly classified point is from the line ___
- answer-The bigger the mistake we've made
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
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
