train_test_split

 TRAIN_TEST_SPLIT spliting ml_data into train test sets

 ARGUMENTS
   x           ...   double array, features for classification.
   y           ...   double array or cell array of char, conditions to classify.
   VariableName...   cell array char, Name of the variables Use this VariableName=table_event.Properties.VariableNames(1:end-2);
   subjects     ...  string cell, subject name of all the subjects.
   subject_wise ...  bool, subject_wise=0 random spliting subject_wise=1 ml_data spliting based on subjects
   split        ...  [0,1], percent of ml_data to be hold out for testing.
   seed         ...  Positive integer. Random seed. Default 0

 RETURNS
   ml_data        ...  Struct containing train, test, Conditions, Classification parameters and etc...