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) IDMaritalRefundTaxableCheatStatusIncomeSingleMarried1.Yes125KNo2No100KNoSingleNo70KNo4MarriedYes120KNo5DivorcedNo95KYes6MarriedNo60KNo7DivorcedSingleYes220KNo8No85KYes9MarriedNo75KNo10SingleNo90KYes

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

See similar textbooks

Related questions

Concept explainers

Question

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
Taxable
Cheat
Status
Income
Single
Married
1.
Yes
125K
No
2
No
100K
No
Single
No
70K
No
4
Married
Yes
120K
No
5
Divorced
No
95K
Yes
6
Married
No
60K
No
7
Divorced
Single
Yes
220K
No
8
No
85K
Yes
9
Married
No
75K
No
10
Single
No
90K
Yes

Expert Solution

Step by step

Solved in 2 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.

Similar questions