There is no one-size-fits-all answer to this question, as the best way to select features in supervised learning problems will vary depending on the specific problem and data set. However, some common methods for feature selection include using domain knowledge to select relevant features, using feature selection algorithms, and using cross-validation to compare different feature sets.
