You are a robot and want to predict the weight of the anteaters based on their skin type, body size and tongue size. You chose to learn a Decision Tree classifier. You are given the following examples Example 1 2 3 4 5 6 7 8 Body Size BIG BIG BIG SMALL BIG SMALL SMALL SMALL Tongue length SHORT LONG SHORT LONG LONG SHORT LONG SHORT Skin type HARD HARD HARD SOFT SOFT HARD HARD HARD Which attribute would information gain choose as the root of the tree? Skin type What is the closest information gain for this attribute? [Select] Weight (lb) 18 16 19 15 12 10 13 14

You are a robot and want to predict the weight of the anteaters based on their skin type, body size and tongue size. You chose to learn a Decision Tree classifier. You are given the following examples Example 1 2 3 4 5 6 7 8 Body Size BIG BIG BIG SMALL BIG SMALL SMALL SMALL Tongue length SHORT LONG SHORT LONG LONG SHORT LONG SHORT Skin type HARD HARD HARD SOFT SOFT HARD HARD HARD Which attribute would information gain choose as the root of the tree? Skin type What is the closest information gain for this attribute? [Select] Weight (lb) 18 16 19 15 12 10 13 14

Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter19: Probabilistic Dynamic Programming

Section19.4: Further Examples Of Probabilistic Dynamic Programming Formulations

Problem 7P

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Concept explainers

Eight puzzle problem

The N-puzzle problem contains N tiles (N+1 including empty tiles) where the value of N can be 8, 15, 24, etc. The puzzle is divided into the square root of (N+1) rows and the square root of (N+1) columns. These problems have an initial state or configuration and a goal state or configuration. The puzzle can be solved by shifting the tiles one by one in the empty space. The objective is to place the numbers on the tiles to match the final state using the empty space. The other name for the N-puzzle problem is the sliding puzzle.

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can someone help me calculate the information gain here please

Full explainthe this question very fast solution sent me step by step
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You are a robot and want to predict the weight of the anteaters based on their skin type, body size
and tongue size. You chose to learn a Decision Tree classifier. You are given the following examples.
Example
1
2
3
4
5
6
7
8
Body Size
BIG
BIG
BIG
SMALL
BIG
SMALL
SMALL
SMALL
Tongue length
SHORT
LONG
SHORT
LONG
LONG
SHORT
LONG
SHORT
Skin type
HARD
HARD
HARD
SOFT
SOFT
HARD
HARD
HARD
Which attribute would information gain choose as the root of the tree?
Skin type
What is the closest information gain for this attribute? [Select]
Weight (lb)
18
16
19
15
12
10
13
14

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