VectorSet (ibi Patterns Learn Library Documentation)

java.lang.Object
- com.tibco.patterns.learn.training.RLinkDataSet<VectorExample>
- - com.tibco.patterns.learn.training.VectorSet

All Implemented Interfaces:

java.lang.Iterable<VectorExample>
```
public final class VectorSet
extends RLinkDataSet<VectorExample>
```
A container for storing a set of VectorExample training examples. Each example contains a feature vector and a label.

- Field Summary
  - Fields inherited from class com.tibco.patterns.learn.training.RLinkDataSet
    examples
- Constructor Summary
  
  Constructors
  Constructor Description
  
  VectorSet(int nFeatures)
  Creates empty dataset.
  
  VectorSet(int nFeatures, int initialCapacity)
  Creates empty dataset.
- Method Summary
  
  All Methods Instance Methods Concrete Methods
  Modifier and Type Method Description
  
  VectorSet createDataSet()
  - Methods inherited from class com.tibco.patterns.learn.training.RLinkDataSet
    add, clearPredictions, getNFeatures, iterator, size, toString, verifyDatasetProportion
  - Methods inherited from class java.lang.Object
    clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
  - Methods inherited from interface java.lang.Iterable
    forEach, spliterator

- Constructor Detail
  - VectorSet
```
public VectorSet(int nFeatures)
```
    Creates empty dataset.
    
    Parameters:
    
    nFeatures - - number of model features in each example of this dataset
  - VectorSet
```
public VectorSet(int nFeatures,
                 int initialCapacity)
```
    Creates empty dataset. Use when the number of examples that will be added is already known.
    
    Parameters:
    
    nFeatures - - number of model features in each example of this dataset
    
    initialCapacity - - number of examples that will be stored in this dataset
- Method Detail
  - createDataSet
```
public VectorSet createDataSet()
```
    Specified by:
    
    createDataSet in class RLinkDataSet<VectorExample>
    
    Returns:
    
    a new empty VectorSet. The number of features is same as for this object.