Write a program that learns a decision tree with the ID3

Added on - 18 Sep 2019

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Write a program that learns a decision tree with the ID3 algorithm. Use your program with the giventraining data (see the cardata on our website). What is your result tree? How are the instancesdistributed in the leaf nodes? Output your learned tree and the distribution of instances in the nodesin an XML-format similar to the one shown below. The solution must be sent until 08:00 am onMonday the 21st of November 2016.<?xml version="1.0" encoding="UTF-8" standalone="no"?><tree classes="class1:123,class2:234,class3:345" entropy="0.123"><node classes="class1:23,class2:123" entropy="0.234" attr1="value1"><node classes="class1:23" entropy="0.0" attr2="value1">class1</node><node classes="class2:123" entropy="0.0" attr2="value2">class2</node></node><node classes="class1:34,class2:45,class3:56" entropy="0.345" attr1="value2">...</node>...</tree>You can see the car data in the attachment.
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