This is a Decision Tree Classification Model Using Entropy Information Gain. What is the depth of the decision tree in * ?this model

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
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entr
This is a Decision Tree Classification
Model Using Entropy Information Gain.
What is the depth of the decision tree in
* ?this model
X122) 0289
entropy0953
samples 426
value (267, 1591
X127) 0502
entropy 0517
samples 302
value 1267, 35S val (0. 1241
entropy00
samples 124
X221 < 0.006
entropy- 0304
samples= 277
value= (262, 15)
XE24] 0678
entropy0.722
samples 25
value 5. 201
entropy 0141
samples 250
value (245. 5
XI21] 032
entropy 0951
samples 27
value- (17, 10)
X19] < 0309
entropy 0.954
samples
value 15. 31
entrapy00
samples 17
value 10. 171
entrepy034
samples 79
value (74. S
entropy00
samples 171
value 171.
entropy 0323
samples 17
value (16. 1
entropy 0.469
samples 10
value 1,9)
entropy 0.811
samples4
value 1.31
entropy 00
samples4
value 14. 01
4
15
14 O
Transcribed Image Text:entr This is a Decision Tree Classification Model Using Entropy Information Gain. What is the depth of the decision tree in * ?this model X122) 0289 entropy0953 samples 426 value (267, 1591 X127) 0502 entropy 0517 samples 302 value 1267, 35S val (0. 1241 entropy00 samples 124 X221 < 0.006 entropy- 0304 samples= 277 value= (262, 15) XE24] 0678 entropy0.722 samples 25 value 5. 201 entropy 0141 samples 250 value (245. 5 XI21] 032 entropy 0951 samples 27 value- (17, 10) X19] < 0309 entropy 0.954 samples value 15. 31 entrapy00 samples 17 value 10. 171 entrepy034 samples 79 value (74. S entropy00 samples 171 value 171. entropy 0323 samples 17 value (16. 1 entropy 0.469 samples 10 value 1,9) entropy 0.811 samples4 value 1.31 entropy 00 samples4 value 14. 01 4 15 14 O
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