Alicia is working with a data set of 438,986 cases which she will use to build a prediction algorithm. Which strategies are acceptable for creating training and validation data sets? Check all that apply. All of the above assuming the cases are ordered, take the first half of the cases for validation and the second half for training None of the above "randomly divide the data set into two equal subsets and use one for training and the other for validation use the same data set for training and validation as it is sufficiently large " split the data set evenly by taking every other row, assuming that the cases are random