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 churn?

The correct answer is A. F1 score. For binary classification tasks like churn prediction, the F1 score balances precision and recall into a single metric, making it ideal for evaluating how well the model identifies churners without over‑ or under‑predicting.

Submitted by jian89· Mar 30, 2026Fundamentals of AI and ML

Question

Options

AF1 score
BMean squared error (MSE)
CR-squared
DTime used to train the model

How the community answered

(32 responses)

A
84% (27)
B
3% (1)
C
9% (3)
D
3% (1)

Explanation

For binary classification tasks like churn prediction, the F1 score balances precision and recall into a single metric, making it ideal for evaluating how well the model identifies churners without over‑ or under‑predicting.

Topics

#F1 score#binary classification#model evaluation#metrics

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