Based on the following confusion matrix with a validation set of 100, class 1 reflects the members targeted who purchased services and class 0 reflects the non-targeted respondents. 77.40% did not purchase services.
For machine learning processes, a classification model's or algorithm's performance is summarized in a confusion matrix, which can be either a chart or a table. Confusion matrix can be useful tools for determining which tasks a machine learning system executes correctly and wrong as well as for predictive analysis.
Specificity rate= TN ÷ (TN + FP) = 48 ÷ (48 + 14) = 0.774
implying 77.40% did not purchase services.
Learn more about specificity rate here:
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