ISYE 6501 - Midterm 1 Exam – Questions And Answers
What do descriptive questions ask?
What do predictive questions ask?
What do prescriptive questions ask?
What is a model?
What do classifiers help you do?
What is a soft classifier and when is it used?
What does it mean when the classifie...
ISYE 6501 - Midterm 1 Exam – Questions And
Answers
1). What do descriptive questions ask?
Ans: What happened? (e.g., which customers are most alike)
2). What do predictive questions ask?
Ans: What will happen? (e.g., what will Google's stock price be?)
3). What do prescriptive questions ask?
Ans: What action(s) would be best? (e.g., where to put traffic lights)
4). What is a model?
Ans: Real-life situation expressed as math.
5). What do classifiers help you do?
Ans: differentiate
6). What is a soft classifier and when is it used?
Ans: 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.
7). What does it mean when the classifier/decision boundary is almost parallel to the vertical
x-axis?
Ans: The horizontal attribute is all that is needed.
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, 8). What does it mean when the classifier/decision boundary is almost parallel to the
horizontal y-axis?
Ans: The vertical attribute is all that is needed.
9). What is time-series data?
Ans: The same data recorded over time often recorded at equal intervals
10). What is quantitative data?
Ans: Number with a meaning: higher means more, lower means less (e.g., age, sales,
temperature, income)
11). What is categorical data?
Ans: Numbers w/o meaning (e.g., zip codes), non-numeric (e.g., hair color), binary
data (e.g., male/female, yes/no, on/off)
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
Ans: A
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
Ans: B
14). What is structured data?
Ans: Data that can be stores in a structured way
15). What is unstructured data?
Ans: Data that is not easily described and stored (e.g., written text)
16). A survey of 25 people recorded each person's family size and type of car. which of these is
a data point?
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, a. the 14th person's family size and car type
b. the 14th person's family size
c.the car type of each person
Ans: A.
A data point is all the information about one observation
17). The farther the wrongly classified point is from the line ___
Ans: The bigger the mistake we've made
18). The term including the margin gets larger so the importance of a large margin out weights
avoiding mistakes and classifying known data samples.
Ans: As lambda gets larger
19). That term also drops towards zero, so the importance of minimizing mistakes and
classifying known data points outweighs having a large margin.
Ans: As lambda drops towards zero
20). What can svms be used for
Ans: to find a classifier with maximum seperation or margin between the two sets of
points?
21). When to use svm?
Ans: If it's impossible to avoid classification errors, SVM can find a classifier that
trades off reducing errors and enlarging the margin.
22). Error for data point j
Ans: What does this formula describe?
23). Total error
Ans: What does this formula describe ?
24). To maximize the distance between the two lines what do we need to minimize?
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, Ans:
25). M_j > 1
Ans: What value do we give for more costly errors
26). Giving a bad loan is twice as costly as withholding a good loan?
Ans: What does this mean in the context of giving a loan?
27). M_j < 1
Ans: What value do we give for less costly errors?
28). Why is it important to scale our data when using svm?
Ans: 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.
29). What does it signify when a coefficient for a classifier is close to zero
Ans: it means the corresponding attribute is probably not relevant
30). What do kernel methods allow for in svms
Ans: nonlinear classifiers
31). What is the common range for scaled data?
Ans: between 0 and 1
32). What is the formula for min-max scaling?
Ans: find min and max for a factor
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