USE INFORMATION GAIN DECISION TREE ALGORITHM TO CONSTRUCT TREE FROM THE GIVEN DA

Question

USE INFORMATION GAIN DECISION TREE ALGORITHM TO CONSTRUCT TREE FROM THE GIVEN DATA SET!!!

Q1. The following table consists of training data from an employee database. 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 sales sales systems systems systems systems marketing senior 36...40 46K...50K 10 marketing junior 31...35 41K...45K 4 senior 31...35 46K...50K30 junior 26...30 26K...30K 40 junior 31...35 31K...35K 40 junior 21...25 46K...50K 20 senior 31...35 66K... 70K5 junior 26...30 46K...50K 3 senior 41...45 66K... 70K 3 secretarysenior 46...50 36K...40K 4 secretaryjunior 26...30 26K...30K 6 Use the Information Gain decision tree algorithm to construct a decision tree from the given data

Explanation / Answer

=> Constructing a decision tree is all about finding attribute that returns the highest information gain.
=> The understanding level of Decision Trees algorithm is very easy compared to other classification algorithms.
=> The decision tree algorithm tries to solve the problem, by reprenting it as tree
=> By using information gain as a criterion, we try to estimate the information contained by each attribute.

=> The basic decision tree algorithm should be modified as follows to take into consideration the count ofeach generalized data tuple.

(salary = 26K...30K:
junior
= 31K...35K:
junior
= 36K...40K:
senior
= 41K...45K:
junior
= 46K...50K (department = secretary:
junior
= sales:
senior
= systems:
junior

= marketing:

senior)

= 66K...70K:

senior)
Take the count into consideration to determine the most common class among the tuples.

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