Alternating conditional expectations

In statistics, Alternating Conditional Expectations (ACE) is a nonparametric algorithm used in regression analysis to find the optimal transformations for both the outcome (response) variable and the input (predictor) variables.^[1]

For example, in a model that tries to predict house prices based on size and location, ACE helps by figuring out if, for instance, transforming the size (maybe taking the square root or logarithm) or the location (perhaps grouping locations into categories) would make the relationship easier to model and lead to better predictions. The algorithm iteratively adjusts these transformations until it finds the ones that maximize the predictive power of the regression model.