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A financial services company is building machine learning models to predict customer churn and detect fraudulent transactions. The data science team is exploring different machine learning approaches and needs to understand which methods fall under supervised learning, where the model is trained on labeled data with known outcomes. Identifying the correct supervised learning techniques will help the team select the most appropriate models for their predictive tasks. Which of the following are examples of supervised learning? (Select two)