AIF-C01 · Question #180
AIF-C01 Question #180: Real Exam Question with Answer & Explanation
The correct answer is A: F1 score. The company is developing an ML model to predict customer churn, a binary classification task (churn or no churn). The F1 score is an evaluation metric that balances precision and recall, making it suitable for assessing the performance of binary classification models, especially
Question
A company is developing an ML model to predict customer churn. Which evaluation metric will assess the model's performance on a binary classification task such as predicting chum?
Options
- AF1 score
- BMean squared error (MSE)
- CR-squared
- DTime used to train the model
Explanation
The company is developing an ML model to predict customer churn, a binary classification task (churn or no churn). The F1 score is an evaluation metric that balances precision and recall, making it suitable for assessing the performance of binary classification models, especially when dealing with imbalanced datasets, which is common in churn prediction. The F1 score is a metric for evaluating binary classification models, combining precision and recall into a single value. It is particularly useful for tasks like churn prediction, where class imbalance may exist, ensuring the model performs well on both positive and negative classes.
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