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. The validation confusion matrix is given below. Actual Class C1 C2 Predicted Class C1 645 112 C2 255 788 Round your answers to 3 digits after the decimal point. The oversampling factor of C1 is . The oversampling factor of C2 is . Please adjust the above validation confusion matrix for oversampling, and compute the following accuracy measures using the adjusted confusion matrix. The Overall Accuracy is . The Overall Error Rate is . The False Discovery Rate (FDR) is . The False Omission Rate (FOR) is . The Precision is . The Specificity is . The Sensitivity is .

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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. The validation confusion matrix is given below.

	Actual Class
C1	C2
Predicted Class	C1	645	112
C2	255	788

Round your answers to 3 digits after the decimal point.

The oversampling factor of C1 is .

The oversampling factor of C2 is .

Please adjust the above validation confusion matrix for oversampling, and compute the following accuracy measures using the adjusted confusion matrix.

The Overall Accuracy is .

The Overall Error Rate is .

The False Discovery Rate (FDR) is .

The False Omission Rate (FOR) is .

The Precision is .

The Specificity is .

The Sensitivity is .

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