Class MultiLabelDataGenerator

java.lang.Object

org.tribuo.multilabel.example.MultiLabelDataGenerator

public class MultiLabelDataGenerator
extends Object

Generates three example train and test datasets, used for unit testing. They don't necessarily have sensible classification boundaries, it's for testing the machinery rather than accuracy.

Method Summary

Modifier and Type	Method	Description
static Example<MultiLabel>	emptyExample()	Generates an example with no features.
static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<MultiLabel>, Dataset<MultiLabel>>	generateDataset()
static Dataset<MultiLabel>	generateTestData()
static Dataset<MultiLabel>	generateTrainData()
static Example<MultiLabel>	invalidSparseExample()	Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

generateTrainData

public static Dataset<MultiLabel> generateTrainData()

generateTestData

public static Dataset<MultiLabel> generateTestData()

generateDataset

public static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<MultiLabel>, Dataset<MultiLabel>> generateDataset()

invalidSparseExample

public static Example<MultiLabel> invalidSparseExample()

Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class. This should make the example empty at prediction time.

Returns:

An example with features {1:1.0,5:5.0,8:8.0}.

emptyExample

public static Example<MultiLabel> emptyExample()

Generates an example with no features.

Returns:

An example with no features.