The following table shows a small set of predictive model validation results for a classification, model with both actual and propensities.
The following table shows a small set of predictive model validation results for a classification, model with both actual and propensities.
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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
Transcribed Image Text:The following table shows a small set of predictive model validation results for a classification, model with
both actual and propensities.
Actual Class Propensity
Actual
Predictive
C1
0.02
C2
Total
1
0.65
0.38
True Positive (TP) =
1
0.88
True Negative (TN) =
0.43
False Positive (FP) =
0.23
False Negative (FN) =
1
0.51
Total (n) =
0.49
Number of misclassified observations =
0.29
0.21
Use the cutoff value of 0.5 to calculate the following:
1
0.84
Error Rate =
0.04
Sensitivity =
0.11
Specificity =
0.53
0.51
1
0.79
0.51
0.29
0.06
0.21
O O
o o
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