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DATA MINING MIDTERM 1 UPDATED ACTUAL QUESTIONS AND CORRECT ANSWERS

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DATA MINING MIDTERM 1 UPDATED ACTUAL QUESTIONS AND CORRECT ANSWERS Question: 1. True or False After the "evaluation" phase is completed, a data scientist needs to proceed to deployment and cannot go back to update the previous steps because they are final. Answer: False Question: 2. True of False CRISP-DM is enforced to make sure that the experiences of the individual team members (data scientists) will have a significant impact on the output of the data mining process Answer: False Question: 3. Which scenario has data leakage A. Predicting whether a criminal will re-offend in the future. Features include: his/her age, previous offenses, marital status, etc. B. Predicting the salary of a fresh graduate student before he finds a job. Features include: the GPA of the student, degree, major, age, internship experience (if there is any), etc C. Predicting the total amount of money a fundraiser will receive on GoFundMe before posting to Go FundMe. Features include: the characteristics of the project, the personal information of the fundraiser, the total number of donors, time of the year, etc Answer: C The total number of donors is unknown information. Question: 4. Which of the following is not part of the CRISP-DM? Model Evaluation Hiring New Staff Business Understanding Data Preparation Answer: Hiring new staff Question: 5. How Many Categorical Features are shown in the following chart? None of the options 3 1 2 Answer: 2

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DATA MINING MIDTERM 1 UPDATED ACTUAL
QUESTIONS AND CORRECT ANSWERS

Question:
1. True or False
After the "evaluation" phase is completed, a data scientist needs to proceed to deployment and cannot go
back to update the previous steps because they are final.
Answer:
False

Question:
2. True of False
CRISP-DM is enforced to make sure that the experiences of the individual team members (data scientists)
will have a significant impact on the output of the data mining process
Answer:
False

Question:
3. Which scenario has data leakage
A. Predicting whether a criminal will re-offend in the future. Features include: his/her age, previous
offenses, marital status, etc.
B. Predicting the salary of a fresh graduate student before he finds a job. Features include: the GPA of the
student, degree, major, age, internship experience (if there is any), etc
C. Predicting the total amount of money a fundraiser will receive on GoFundMe before posting to Go-
FundMe. Features include: the characteristics of the project, the personal information of the fundraiser, the
total number of donors, time of the year, etc
Answer:
C
The total number of donors is unknown information.

Question:
4. Which of the following is not part of the CRISP-DM?
Model Evaluation Hiring New Staff Business Understanding Data Preparation
Answer:
Hiring new staff

Question:
5. How Many Categorical Features are shown in the following chart?
None of the options
312
Answer:
2

, Question:
6. A histogram is used to show
the range (distribution) of a numerical feature none of these options the count of each category of an
ordinal feature the count of each category of a categorical feature
Answer:
the range (distribution) of a numerical feature

Question:
7. Suppose you are given data with a numerical feature X. We know the following info about X. mean of X
= M = 62 median of X = Med = 70 Max of X = 95 Min of X = 35 Which of the following statement is
correct?
Center of X is 35 50% of the X values are less than Med Range of X is 95 50% of X values are greater than
M
Answer:
50% of X values are less than Med

Question:
8. True of False During the Data Prep step of CRISP-DM, we might have to merge data from different
tables into a single table for modeling.
Answer:
True

Question:
9. Is the sequence of the phases in CRISP Strict?
Answer:
No

Question:
10. Business Understand (CRISP) Overview
Answer:

Question:
11. CRISP Steps
Answer:
Business Understanding, Data Understanding, Data Prep, Modeling, Evaluation, Deployment

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