Train an ID3 decision tree for a dataset shown in the following table. The table contains 2 categorical attributes (refund and marital status) and 1 continuous attribute (taxable income). Once you got the model then use it to classify the input X1 (No, Single, 95K) and X2 (Yes, Divorced, 120K) IDMaritalRefundТаxаbleCheatStatusIncomeSingleYes125KNo2MarriedNo100KNo370KSingleMarriedNoNo4Yes120KNo5DivorcedNo95KYes6MarriedNo60KNo7DivorcedYes220KNo8SingleNo85KYesMarriedNo75KNo10SingleNo90KYes

The following is the python code for ID3 decision tree and predict values. Use Jupyter notebook or…

Answered: Train an ID3 decision tree for a…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Train an ID3 decision tree for a dataset shown in the following table. The table contains 2 categorical attributes (refund and marital status) and 1 continuous attribute (taxable income). Once you got the model then use it to classify the input X1 (No, Single, 95K) and X2 (Yes, Divorced, 120K)

ID
Marital
Refund
Таxаble
Cheat
Status
Income
Single
Yes
125K
No
2
Married
No
100K
No
3
70K
Single
Married
No
No
4
Yes
120K
No
5
Divorced
No
95K
Yes
6
Married
No
60K
No
7
Divorced
Yes
220K
No
8
Single
No
85K
Yes
Married
No
75K
No
10
Single
No
90K
Yes

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