Isye 6501 Final exam 2023-2024| Isye 6501Test
Bank Questions and Correct Answers Rated A+
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
What can SVMs be used for - ANSWER>>to find a classifier with maximum
seperation or margin between the two sets of points?
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.
Error for data point j - ANSWER>>What does this formula describe?
Total error - ANSWER>>What does this formula describe ?
To maximize the distance between the two lines what do we need to minimize?
- ANSWER>>
m_j > 1 - ANSWER>>What value do we give for more costly errors
Giving a bad loan is twice as costly as withholding a good loan? -
ANSWER>>What does this mean in the context of giving a loan?
m_j < 1 - ANSWER>>What value do we give for less costly errors?
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
Bank Questions and Correct Answers Rated A+
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
What can SVMs be used for - ANSWER>>to find a classifier with maximum
seperation or margin between the two sets of points?
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.
Error for data point j - ANSWER>>What does this formula describe?
Total error - ANSWER>>What does this formula describe ?
To maximize the distance between the two lines what do we need to minimize?
- ANSWER>>
m_j > 1 - ANSWER>>What value do we give for more costly errors
Giving a bad loan is twice as costly as withholding a good loan? -
ANSWER>>What does this mean in the context of giving a loan?
m_j < 1 - ANSWER>>What value do we give for less costly errors?
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
