What are common feature selection methods in regression task?

In regression tasks, common feature selection methods include:
Option A: correlation coefficient - This method evaluates the strength and direction of the linear relationship between each feature and the target variable.
Option B: greedy algorithms - Greedy algorithms iteratively select features based on certain criteria, such as maximizing predictive performance or minimizing error.
Therefore, Option C encompasses both of these common feature selection methods, making it the correct choice.