Holdout (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

All Known Implementing Classes:

AbstractHoldout, DisjointCrossValidation, LeaveOneOut, RandomizedCrossValidation, RandomizedHoldout, StratifiedCrossValidation
```
public interface Holdout
```
A holdout procedure is to provide a range of partitions of a database to pairs of training and test data sets.

Since:

0.7.0

Author:

Erich Schubert

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`java.util.ArrayList<ClassLabel>`	`getLabels()`	Get the sorted class labels present in this data set.
`void`	`initialize(MultipleObjectsBundle bundle)`	Initialize the holdout procedure for a data set.
`TrainingAndTestSet`	`nextPartitioning()`	Get the next partitioning of the given holdout.
`int`	`numberOfPartitions()`	How many partitions to test.

- Method Detail
  - initialize
```
void initialize(MultipleObjectsBundle bundle)
```
    Initialize the holdout procedure for a data set.
    
    Parameters:
    
    bundle - Data set bundle
  - nextPartitioning
```
TrainingAndTestSet nextPartitioning()
```
    Get the next partitioning of the given holdout.
    
    Returns:
    
    Next partitioning of the data set
  - getLabels
```
java.util.ArrayList<ClassLabel> getLabels()
```
    Get the sorted class labels present in this data set. For indexing into assignment arrays.
    
    Returns:
    
    Class labels
  - numberOfPartitions
```
int numberOfPartitions()
```
    How many partitions to test.
    
    Returns:
    
    Number of partitions.