Which of the following best describes the purpose of cross-validation in supervised learning? Which of the following best describes the purpose of cross-validation in supervised learning? To randomly shuffle the data before training the model To split the data into training and holdout sets To reduce the dimensionality of the feature space To reduce the likelihood of making conclusions that are idiosyncratic to how the individual data points were assigned to the different sets in the partition