The following table consists of training data from an employee database. The data have been generalized. For example, "31 ... 35" for age represents the age range of 31 to 35. For a given row entry, count represents the number of data tuples having the values for department, status, age, and salary given in that row. department status salary age соunt sales senior 31...35 46K...50K 30 sales junior 26... 30 26K...30K 40 sales junior 31...35 31K...35K 40 systems junior 21...25 46K...50K 20 systems senior 31...35 66K...70K 5 systems junior 26... 30 46K...50K 3 systems senior 41...45 66K...70K 3 marketing marketing junior 31...35 senior 36...40 46K...50K 10 41K...45K 4 secretary senior 46...50 36K...40K 4 secretary junior 26...30 26K...30K 6. Let status be the class label attribute. 1. Make RULES-BASED CLASIFICATION

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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  1. Make RULES-BASED CLASIFICATION

Reference :

Data Mining. Concepts and Techniques, 3rd Edition by Jiawei Han, Micheline Kamber, Jian Pei

The following table consists of training data from an employee database. The data have
been generalized. For example, "31... 35" for age represents the age range of 31 to 35.
For a given row entry, count represents the number of data tuples having the values for
department, status, age, and salary given in that row.
department status
age
salary
count
sales
senior
31...35
46K...50K
30
junior 26... 30
junior 31...35
sales
26K...30K
40
sales
31K...35K
40
systems
junior 21...25
46K...50K
20
systems
senior 31...35
66K...70K
5
systems
junior 26...30
46K...50K
3
systems
senior
41...45
66K...70K
3
marketing
senior 36...40
46K...50K
10
marketing junior 31...35
41K...45K
4
secretary
senior
46...50
36K...40K
4
secretary
junior
26...30
26K...30K
6
Let status be the class label attribute.
1. Make RULES-BASED CLASIFICATION
Transcribed Image Text:The following table consists of training data from an employee database. The data have been generalized. For example, "31... 35" for age represents the age range of 31 to 35. For a given row entry, count represents the number of data tuples having the values for department, status, age, and salary given in that row. department status age salary count sales senior 31...35 46K...50K 30 junior 26... 30 junior 31...35 sales 26K...30K 40 sales 31K...35K 40 systems junior 21...25 46K...50K 20 systems senior 31...35 66K...70K 5 systems junior 26...30 46K...50K 3 systems senior 41...45 66K...70K 3 marketing senior 36...40 46K...50K 10 marketing junior 31...35 41K...45K 4 secretary senior 46...50 36K...40K 4 secretary junior 26...30 26K...30K 6 Let status be the class label attribute. 1. Make RULES-BASED CLASIFICATION
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