Class CRFLabeler<T>

java.lang.Object

smile.sequence.CRFLabeler<T>

Type Parameters:

T - the data type of model input objects.

All Implemented Interfaces:

Serializable, SequenceLabeler<T>

public class CRFLabeler<T>
extends Object
implements SequenceLabeler<T>

First-order CRF sequence labeler.

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
CRFLabeler(CRF model, Function<T,Tuple> features)	Constructor.

Method Summary

Modifier and Type	Method	Description
static <T> CRFLabeler<T>	fit(T[][] sequences, int[][] labels, Function<T,Tuple> features)	Fits a CRF model.
static <T> CRFLabeler<T>	fit(T[][] sequences, int[][] labels, Function<T,Tuple> features, CRF.Options options)	Fits a CRF.
int[]	predict(T[] o)	Returns the most likely label sequence given the feature sequence by the forward-backward algorithm.
String	toString()
int[]	viterbi(T[] o)	Labels sequence with Viterbi algorithm.

Methods inherited from class Object

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

Constructor Details

CRFLabeler

public CRFLabeler(CRF model,
 Function<T,Tuple> features)

Constructor.

Parameters:

model - the CRF model.

features - the feature function.

Method Details

fit

public static <T> CRFLabeler<T> fit(T[][] sequences,
 int[][] labels,
 Function<T,Tuple> features)

Fits a CRF model.

Type Parameters:

T - the data type of observations.

Parameters:

sequences - the training data.

labels - the training sequence labels.

features - the feature function.

Returns:

the model.

fit

public static <T> CRFLabeler<T> fit(T[][] sequences,
 int[][] labels,
 Function<T,Tuple> features,
 CRF.Options options)

Fits a CRF.

Type Parameters:

T - the data type of observations.

Parameters:

sequences - the observation sequences.

labels - the state labels of observations, of which states take values in [0, k), where k is the number of hidden states.

features - the feature function.

options - the hyperparameters.

Returns:

the model.

toString

public String toString()

Overrides:

toString in class Object

predict

public int[] predict(T[] o)

Returns the most likely label sequence given the feature sequence by the forward-backward algorithm.

Specified by:

predict in interface SequenceLabeler<T>

Parameters:

o - the observation sequence.

Returns:

the most likely state sequence.

viterbi

public int[] viterbi(T[] o)

Labels sequence with Viterbi algorithm. Viterbi algorithm returns the whole sequence label that has the maximum probability, which makes sense in applications (e.g.part-of-speech tagging) that require coherent sequential labeling. The forward-backward algorithm labels a sequence by individual prediction on each position. This usually produces better accuracy although the results may not be coherent.

Parameters:

o - the observation sequence.

Returns:

the sequence labels.