org.tribuo.anomaly.example

Class AnomalyDataGenerator

java.lang.Object

org.tribuo.anomaly.example.AnomalyDataGenerator

public abstract class AnomalyDataGenerator
extends Object

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

Also has a dataset generator which returns a training dataset with no anomalies sampled from a single gaussian, and a test dataset sampled from two gaussians where the second is labelled anomalous.

Constructor Summary

Constructors

Constructor and Description
AnomalyDataGenerator()

Method Summary

Modifier and Type	Method and Description
static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>>	denseTrainTest() Makes a simple dataset for training and testing.
static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>>	denseTrainTest(double negate) Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}, and there are 4 clusters, {0,1,2,3}.
static Example<Event>	emptyExample() Generates an example with no features.
static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>>	gaussianAnomaly() Generates two datasets, one without anomalies drawn from a single gaussian and the second drawn from a mixture of two gaussians, with the second tagged anomalous.
static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>>	gaussianAnomaly(long size, double fractionAnomalous) Generates two datasets, one without anomalies drawn from a single gaussian and the second drawn from a mixture of two gaussians, with the second tagged anomalous.
static Example<Event>	invalidSparseExample() Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>>	sparseTrainTest() Makes a simple dataset for training and testing.
static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>>	sparseTrainTest(double negate) Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data.

Methods inherited from class java.lang.Object

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

Constructor Detail

AnomalyDataGenerator

public AnomalyDataGenerator()

Method Detail

gaussianAnomaly

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

Generates two datasets, one without anomalies drawn from a single gaussian and the second drawn from a mixture of two gaussians, with the second tagged anomalous. Generates 200 training examples and 200 test examples, with 20% anomalies.

Returns:

A pair of datasets.

gaussianAnomaly

public static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>> gaussianAnomaly(long size,
                                                                                                  double fractionAnomalous)

Generates two datasets, one without anomalies drawn from a single gaussian and the second drawn from a mixture of two gaussians, with the second tagged anomalous.

Parameters:

size - The number of points to sample for each dataset.

fractionAnomalous - The fraction of anomalous data to generate.

Returns:

A pair of datasets.

denseTrainTest

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

Makes a simple dataset for training and testing.

Used for smoke testing, doesn't have a real boundary.

Returns:

A pair containing a training dataset and a testing dataset.

denseTrainTest

public static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>> denseTrainTest(double negate)

Generates a train/test dataset pair which is dense in the features, each example has 4 features,{A,B,C,D}, and there are 4 clusters, {0,1,2,3}.

Parameters:

negate - Supply -1.0 to negate some feature values.

Returns:

A pair of datasets.

sparseTrainTest

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

Makes a simple dataset for training and testing.

Used for smoke testing, doesn't have a real boundary.

Returns:

A pair containing a training dataset and a testing dataset.

sparseTrainTest

public static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<Event>,Dataset<Event>> sparseTrainTest(double negate)

Generates a pair of datasets, where the features are sparse, and unknown features appear in the test data. It has the same 4 clusters {0,1,2,3}.

Parameters:

negate - Supply -1.0 to negate some feature values.

Returns:

A pair of datasets.

invalidSparseExample

public static Example<Event> 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<Event> emptyExample()

Generates an example with no features.

Returns:

An example with no features.