Amazon
MLS-C01 · Question #54
A Data Scientist is evaluating different binary classification models. A false positive result is 5 times more expensive (from a business perspective) than a false negative result. The models should…
The correct answer is D. TN = 98, FP = 2. The following calculations are required: TP = True Positive FP = False Positive FN = False Negative TN = True Negative FN = False Negative Recall = TP / (TP + FN) False Positive Rate (FPR) = FP / (FP + TN) Cost = 5 * FP + FN Options C and D have a recall greater than 80% and an…
Modeling
Question
A Data Scientist is evaluating different binary classification models. A false positive result is 5 times more expensive (from a business perspective) than a false negative result. The models should be evaluated based on the following criteria: 1) Must have a recall rate of at least 80% 2) Must have a false positive rate of 10% or less 3) Must minimize business costs After creating each binary classification model, the Data Scientist generates the corresponding confusion matrix. Which confusion matrix represents the model that satisfies the requirements?
Exhibit
Options
- ATN = 91, FP = 9
- BTN = 99, FP = 1
- CTN = 96, FP = 4
- DTN = 98, FP = 2
How the community answered
(36 responses)- A8% (3)
- B11% (4)
- C31% (11)
- D50% (18)
Explanation
The following calculations are required: TP = True Positive FP = False Positive FN = False Negative TN = True Negative FN = False Negative Recall = TP / (TP + FN) False Positive Rate (FPR) = FP / (FP + TN) Cost = 5 * FP + FN Options C and D have a recall greater than 80% and an FPR less than 10%, but D is the most
Topics
#Confusion Matrix#Classification Metrics#Cost-sensitive Learning#Model Evaluation
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