Consider the training dataset given in Table P3.5. a. Construct a decision tree from the given data using "information gain" based splitting. Table P3.5 D3 D4 DS D6 07 DB Day D10 011 012 D13 D14 sunny sunny overcast rain rain Outlook rain overcast sunny sunny rain sunny overcast overcast rain hot hot hot mild cool cool cool mild cool mild mild mild hot mild Temperature high high high high normal normal Humidity normal high normal normal normal high normal high (Outlook- sunny, Temperature cool, Humidity high, Wind -strong) Wind weak strong weak weak weak strong strong weak weak weak strong strong weak strong no yes yes yes no yes no yes yes yes yes no PlayTennis

Consider the training dataset given in Table P3.5. a. Construct a decision tree from the given data using "information gain" based splitting. Table P3.5 D3 D4 DS D6 07 DB Day D10 011 012 D13 D14 sunny sunny overcast rain rain Outlook rain overcast sunny sunny rain sunny overcast overcast rain hot hot hot mild cool cool cool mild cool mild mild mild hot mild Temperature high high high high normal normal Humidity normal high normal normal normal high normal high (Outlook- sunny, Temperature cool, Humidity high, Wind -strong) Wind weak strong weak weak weak strong strong weak weak weak strong strong weak strong no yes yes yes no yes no yes yes yes yes no PlayTennis

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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