ID Major Avg. project score Avg. exam score Employed? Salary Computer 82 76 Yes 90,000 Engineering 84 94 Yes 75,000 3. Engineering 73 65 No Math 71 No Computer 92 75 Yes 95,000 For each of the following tasks, describe (briefly) what, if anything, you would need to do to the above dataset before using any learning algorithm to predict if someone will be employed following graduation. a) Data cleaning b) Data integration c) Data transformation d) Data reduction e) Data discretization
ID Major Avg. project score Avg. exam score Employed? Salary Computer 82 76 Yes 90,000 Engineering 84 94 Yes 75,000 3. Engineering 73 65 No Math 71 No Computer 92 75 Yes 95,000 For each of the following tasks, describe (briefly) what, if anything, you would need to do to the above dataset before using any learning algorithm to predict if someone will be employed following graduation. a) Data cleaning b) Data integration c) Data transformation d) Data reduction e) Data discretization
C++ for Engineers and Scientists
4th Edition
ISBN:9781133187844
Author:Bronson, Gary J.
Publisher:Bronson, Gary J.
Chapter11: Introduction To Classes
Section11.5: A Closer Look: Uml Class And Object Diagrams
Problem 6E
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Computer Science
please help i only have 15 min
![Problem 1:
Major
Avg. project score
Avg. exam score
Employed?
Salary
ID
Computer
82
76
Yes
90,000
Engineering
84
94
Yes
75,000
3
Engineering
73
65
No
Math
71
No
Computer
92
75
Yes
95,000
For each of the following tasks, describe (briefly) what, if anything, you would need to do to the above
dataset before using any learning algorithm to predict if someone will be employed following
graduation.
a) Data cleaning
b) Data integration
c) Data transformation
d) Data reduction
e) Data discretization](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F8d7b5626-12a4-465e-9b72-0c15fb0e4930%2F2ecd1840-e8f3-4e95-9e9a-0d0ffceaa1c0%2Fl2u4vii_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Problem 1:
Major
Avg. project score
Avg. exam score
Employed?
Salary
ID
Computer
82
76
Yes
90,000
Engineering
84
94
Yes
75,000
3
Engineering
73
65
No
Math
71
No
Computer
92
75
Yes
95,000
For each of the following tasks, describe (briefly) what, if anything, you would need to do to the above
dataset before using any learning algorithm to predict if someone will be employed following
graduation.
a) Data cleaning
b) Data integration
c) Data transformation
d) Data reduction
e) Data discretization
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