7. Assume there are 3,600 cases in the validation dataset, and 12% of these cases have a value of 1 for churn (the primary/positive event). Questions a) to c) are based on data for the 3,600 cases (see table below). Model Decision Tree Logistic Regression Neural Network Decision Tree Logistic Regression Neural Network Decision Tree Logistic Regression Neural Network Decision Tree Logistic Regression Neural Network Depth (% Contacted) 5 5 5 10 10 10 15 15 15 20 20 20 Cumulative Gain Cumulative Lift 34.42 6.84 20.19 4.01 34.62 6.88 64.90 36.06 62.50 73.96 49.04 82.21 78.39 59.13 86.54 6.06 3.15 5.54 1.82 2.62 3.97 0.87 2.01 0.86

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
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Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 30PPS
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If the Cumulative Gain at a depth of 10% for the Decision Tree is converted to number of primary/positive event cases, what will be the number of cases?  Show your calculation

7. Assume there are 3,600 cases in the validation dataset, and 12% of these cases have a value of 1 for
churn (the primary/positive event). Questions a) to c) are based on data for the 3,600 cases (see table
below).
Model
Decision Tree
Logistic Regression
Neural Network
Decision Tree
Logistic Regression
Neural Network
Decision Tree
Logistic Regression
Neural Network
Decision Tree
Logistic Regression
Neural Network
Depth
(% Contacted)
5
5
5
10
10
10
15
15
15
20
20
20
Cumulative Gain Cumulative Lift
34.42
6.84
20.19
4.01
34.62
6.88
64.90
36.06
62.50
73.96
49.04
82.21
78.39
59.13
86.54
6.06
3.15
5.54
1.82
2.62
3.97
0.87
2.01
0.86
Transcribed Image Text:7. Assume there are 3,600 cases in the validation dataset, and 12% of these cases have a value of 1 for churn (the primary/positive event). Questions a) to c) are based on data for the 3,600 cases (see table below). Model Decision Tree Logistic Regression Neural Network Decision Tree Logistic Regression Neural Network Decision Tree Logistic Regression Neural Network Decision Tree Logistic Regression Neural Network Depth (% Contacted) 5 5 5 10 10 10 15 15 15 20 20 20 Cumulative Gain Cumulative Lift 34.42 6.84 20.19 4.01 34.62 6.88 64.90 36.06 62.50 73.96 49.04 82.21 78.39 59.13 86.54 6.06 3.15 5.54 1.82 2.62 3.97 0.87 2.01 0.86
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