Estimation Procedure type

http://openml.org/openml/estimationProcedure-type : A-Z

• Cross validation

  • DEF : Cross-validation or ‘k-fold cross-validation’ is when the dataset is randomly split up into ‘k’ groups. One of the groups is used as the test set and the rest are used as the training set.
• Custom Holdout
• Holdout

  • DEF : Hold-out is when a dataset is split into a ‘train’ and ‘test’ set
• Holdout ordered
• Holdout unlabeled
• Leave one out

  • DEF : Leave one out is a cross validation where k is equal the number of records in the entire dataset
• Test on training data
• Test then train