Question
Evaluating Predictive Performance ( Business Analytics) Confusion Matrix !!! A publisher plans to boost the sales...
Evaluating Predictive Performance ( Business Analytics)
Confusion Matrix !!!
- A publisher plans to boost the sales of its most popular magazine by sending out promotional mails. We refer to a customer as a responder if he/she subscribes to the magazine for the next year after receiving a promotional mail. Otherwise the customer is referred to as a non-responder. Denote responder by C1 and non-responder by C2. The publisher has built a model to classify each customer as either a responder or a non-responder. In practice only 1% of the customers are responders, and the remaining 99% are non-responders. In order to build an unbiased model, the publisher employed the oversampling method in creating the training set and the validation set, such that both datasets contain 50% responders and 50% non-responders. Please adjust the following validation confusion matrix for oversampling, then compute accuracy measures using the adjusted confusion matrix. Keep at least three digits after the decimal point.
Actual Class | |||
C1 | C2 | ||
Predicted Class | C1 | 645 | 112 |
C2 | 255 | 788 |
Oversampling factor of C1: | |
Oversampling factor of C2: |
Adjusted validation confusion matrix:
Actual Class | |||
C1 | C2 | ||
Predicted Class | C1 | ||
C2 |
Overall Accuracy | |
Overall Error Rate | |
False Discovery Rate (FDR) | |
False Omission Rate (FOR) | |
Precision | |
Specificity | |
Sensitivity |
Answers
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