PairSampleIterator (Mallet 2 API)

java.lang.Object
- cc.mallet.cluster.iterator.NeighborIterator
- - cc.mallet.cluster.iterator.PairSampleIterator

All Implemented Interfaces:

java.util.Iterator<Instance>

Direct Known Subclasses:

ClusterSampleIterator
```
public class PairSampleIterator
extends NeighborIterator
```
Sample pairs of Instances.

Since:

1.0

Version:

1.0

Author:

"Aron Culotta"

See Also:

NeighborIterator

Field Summary

Fields
Modifier and Type	Field	Description
`protected InstanceList`	`instances`
`protected int[]`	`nonsingletonClusters`
`protected int`	`numberSamples`
`protected int`	`positiveCount`
`protected double`	`positiveProportion`
`protected int`	`positiveTarget`
`protected Randoms`	`random`
`protected int`	`totalCount`

Fields inherited from class cc.mallet.cluster.iterator.NeighborIterator
clustering

Constructor Summary

Constructors
Constructor	Description
`PairSampleIterator(Clustering clustering, Randoms random, double positiveProportion, int numberSamples)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type Method Description

boolean hasNext()

Instance next()
- Methods inherited from class cc.mallet.cluster.iterator.NeighborIterator
  getClustering, remove
- Methods inherited from class java.lang.Object
  clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
- Methods inherited from interface java.util.Iterator
  forEachRemaining

Field Detail

instances
```
protected InstanceList instances
```

random
```
protected Randoms random
```

positiveProportion
```
protected double positiveProportion
```

numberSamples
```
protected int numberSamples
```

positiveTarget
```
protected int positiveTarget
```

positiveCount
```
protected int positiveCount
```

totalCount
```
protected int totalCount
```

nonsingletonClusters
```
protected int[] nonsingletonClusters
```

Constructor Detail
- PairSampleIterator
```
public PairSampleIterator(Clustering clustering,
                          Randoms random,
                          double positiveProportion,
                          int numberSamples)
```
  Parameters:
  
  clustering - True clustering.
  
  random - Source of randomness.
  
  positiveProportion - Proportion of Instances that should be positive examples.
  
  numberSamples - Total number of samples to generate.

Method Detail

hasNext
```
public boolean hasNext()
```

next
```
public Instance next()
```