- The overall entropy is (round to 2 decimals): - The information gain for attribute A is (round to 2 decimals):  - The information gain for attribute B is (round to 2 decimals):  -The information gain for attribute C is (round to 2 decimals):

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Chapter3: Performing Calculations With Formulas And Functions
Section: Chapter Questions
Problem 3.9CP
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- The overall entropy is (round to 2 decimals):

- The information gain for attribute A is (round to 2 decimals): 

- The information gain for attribute B is (round to 2 decimals): 

-The information gain for attribute C is (round to 2 decimals):

Conditional Entropies
H(Y|A=0)=0.92
H(Y|A=0, B=0)=0.00
H(Y|A=1, C=0)=0.00
H(Y|A=1)=0.86
H(Y|A=0, B=1)=0.00
H(Y|A=1, C=1)=0.92
H(Y|B=0)=0.00
H(Y|A=1, B=0)=0.00
H(Y|B=0, C=0)=0.00
H(Y|B=1)=0.99
H(Y|A=1, B=1)=0.97
H(Y|B=0, C=1)=0.92
H(Y|C=0)=0.72
H(Y|A=0, C=0)=0.00
H(Y|B=1, C=0)=0.00
H(Y|C=1)=0.97
H(Y|A=0, C=1)=0.81
H(Y|B=1, C=1)=0.81
Transcribed Image Text:Conditional Entropies H(Y|A=0)=0.92 H(Y|A=0, B=0)=0.00 H(Y|A=1, C=0)=0.00 H(Y|A=1)=0.86 H(Y|A=0, B=1)=0.00 H(Y|A=1, C=1)=0.92 H(Y|B=0)=0.00 H(Y|A=1, B=0)=0.00 H(Y|B=0, C=0)=0.00 H(Y|B=1)=0.99 H(Y|A=1, B=1)=0.97 H(Y|B=0, C=1)=0.92 H(Y|C=0)=0.72 H(Y|A=0, C=0)=0.00 H(Y|B=1, C=0)=0.00 H(Y|C=1)=0.97 H(Y|A=0, C=1)=0.81 H(Y|B=1, C=1)=0.81
1. Decision Trees
The dataset below contains three input attributes, A, B, C, and one class attribute, Y. For your convenience,
the conditional entropies computed from this dataset are also shown:
|ABCY
110 True
1 01
0 11 |False
11|False
10
0 0 0 True
10 False
11 | False
00
1 1
True
1
True
1
1
True
1
True
Transcribed Image Text:1. Decision Trees The dataset below contains three input attributes, A, B, C, and one class attribute, Y. For your convenience, the conditional entropies computed from this dataset are also shown: |ABCY 110 True 1 01 0 11 |False 11|False 10 0 0 0 True 10 False 11 | False 00 1 1 True 1 True 1 1 True 1 True
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