There appears to be an error in the calculation of False Negatives (FN) and False Positives (FP) in the given explanation. Here is the corrected calculation for accuracy:
Exhibit 2. Confusion Matrix: Preliminary Model
Accuracy = (TP + TN) / (TP + FP + TN + FN)
Accuracy = (371 + 591) / (371 + 208 + 591 + 198)
Accuracy = 962 / 1368
Accuracy = 0.7037 (approximately)
So, the accuracy of the preliminary model is closest to 0.70, not 0.64 or 0.65 as originally suggested. Therefore, option C is the correct answer.
There appears to be an error in the calculation of False Negatives (FN) and False Positives (FP) in the given explanation. Here is the corrected calculation for accuracy:
Exhibit 2. Confusion Matrix: Preliminary Model
Accuracy = (TP + TN) / (TP + FP + TN + FN)
Accuracy = (371 + 591) / (371 + 208 + 591 + 198)
Accuracy = 962 / 1368
Accuracy = 0.7037 (approximately)
So, the accuracy of the preliminary model is closest to 0.70, not 0.64 or 0.65 as originally suggested. Therefore, option C is the correct answer.