hw02 - d) Convert the decision tree into the rules. Q4)...

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CS464 Introduction to Machine Learning Fall 2009 Homework 2 – Decision Tree Learning Due Date: October 23, 2009 Q1) Give decision trees to represent the following boolean functions: A ¬ B A [B C] A XOR B [A B] [C D] Q2) Consider the following set of training examples: a) What is the entropy of this collection of training examples with respect to the target function classification? b) What is the information gain of a2 relative to these training examples? c) Create the decision tree for these training examples using ID3. Q3) Consider the following set of training examples: Instance Classification Attrb1 Attrb2 Attrb3 1 c1 a T a 2 c1 a T b 3 c2 b F c 4 c1 c T d 5 c3 a F a 6 c3 b T b 7 c2 c F c 8 c2 b T c 9 c1 a T a 10 c1 b F b a) What is the entropy of this collection of training examples with respect to the target function classification? b) What is the information gain of Attrb1 relative to these training examples? c) Create the decision tree for these training examples using ID3.
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Unformatted text preview: d) Convert the decision tree into the rules. Q4) Consider the following set of training examples: Instance Classification Attrb1 Attrb2 1 T 4 F 2 T 10 T 3 F 20 F 4 F 34 T 5 F 50 F 6 F 70 F 7 T 76 F 8 T 80 T 9 F 90 T 10 F 92 T a) Create the decision tree for these training examples using ID3. Note that Attrb1 is a continuous-valued attribute. b) Convert the decision tree into the rules. You should hand-in: Give the hard copy (type-written) of your homework on due date in the class. Send the soft copy (word document, or pdf) of your homework to your assistant. Make sure that your homework contains your name, and the subject field of your email is Homework1 (email to your assistant (Mcahid Kutlu) mucahid@cs.bilkent.edu.tr ). DO IT YOURSELF CHEATING WILL BE PUNISHED...
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This note was uploaded on 12/27/2009 for the course CS 464 taught by Professor Demir during the Fall '08 term at Bilkent University.

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hw02 - d) Convert the decision tree into the rules. Q4)...

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