Question 1 of 30
A data scientist is tasked with building a predictive model using Azure Machine Learning. The model needs to predict customer churn based on various features such as customer demographics, usage patterns, and service interactions. The data scientist decides to use a classification algorithm and needs to evaluate the model\'s performance. Which metric would be most appropriate for assessing the model\'s effectiveness in predicting customer churn, especially considering the potential class imbalance in the dataset?
F1 Score
Mean Absolute Error
Root Mean Squared Error
R-squared

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