ClassificationResult

public abstract class ClassificationResult

Represents the classification results of a model. Typically used as a result for classification tasks.

Public Constructors

ClassificationResult()

Public Methods

abstract List<Classifications>	classifications() The classification results for each head of the model.
static ClassificationResult	create(List<Classifications> classifications, Optional<Long> timestampMs) Creates a ClassificationResult instance.
static ClassificationResult	createFromProto(ClassificationsProto.ClassificationResult proto) Creates a ClassificationResult object from a ERROR(/ClassificationsProto.ClassificationResult) protobuf message.
abstract Optional<Long>	timestampMs() The optional timestamp (in milliseconds) of the start of the chunk of data corresponding to these results.

Inherited Methods

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

Public Constructors

public ClassificationResult ()

Public Methods

public abstract List<Classifications> classifications ()

The classification results for each head of the model.

public static ClassificationResult create (List<Classifications> classifications, Optional<Long> timestampMs)

Creates a ClassificationResult instance.

Parameters

classifications	the list of Classifications objects containing the predicted categories for each head of the model.
timestampMs	the optional timestamp (in milliseconds) of the start of the chunk of data corresponding to these results.

public static ClassificationResult createFromProto (ClassificationsProto.ClassificationResult proto)

Creates a ClassificationResult object from a ERROR(/ClassificationsProto.ClassificationResult) protobuf message.

Parameters

proto	the ERROR(/ClassificationsProto.ClassificationResult) protobuf message to convert.

public abstract Optional<Long> timestampMs ()

The optional timestamp (in milliseconds) of the start of the chunk of data corresponding to these results.

This is only used for classification on time series (e.g. audio classification). In these use cases, the amount of data to process might exceed the maximum size that the model can process: to solve this, the input data is split into multiple chunks starting at different timestamps.