machine-learning video for you are a data scientist working on a loan approval model for a bank. The model predicts whether a loan application should be
You are a data scientist working on a loan approval model for a bank. The model predicts whether a loan application should be approved or rejected based on various features such as income, credit score, and employment history. The bank is particularly concerned about ensuring that the model is fair and does not discriminate against any demographic group, such as age, gender, or ethnicity. To address this, you need to select the appropriate evaluation metrics to assess both the model’s performance and any potential bias. Given these requirements, which combination of evaluation metrics and bias detection methods is MOST APPROPRIATE for ensuring fair and accurate model predictions?