So I am trying to implement Bayesian optimization for various machine learning methods, all of then consist of hyperparameters which should be tuned (eg. complexity parameter, minimum samples in split etc in decision tree, ....). According to help about function from R package rBayesianOptimization we have to specify
"FUN: The function to be maximized. This Function should return a named list with 2 components. The first component "Score" should be the metrics to be maximized, and the second component "Pred" should be the validation/cross-validation prediction for ensembling/stacking. "
So what will be the Score component, for example for this decision tree ?