Class NluSettings.Builder (0.94.0)

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public static final class NluSettings.Builder extends GeneratedMessage.Builder<NluSettings.Builder> implements NluSettingsOrBuilder

Settings related to NLU.

Protobuf type google.cloud.dialogflow.cx.v3beta1.NluSettings

Inheritance

java.lang.Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessage.Builder > NluSettings.Builder

Implements

NluSettingsOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessage.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessage.Builder.clear()

GeneratedMessage.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessage.Builder.clone()

GeneratedMessage.Builder.getAllFields()

GeneratedMessage.Builder.getDescriptorForType()

GeneratedMessage.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessage.Builder.getParentForChildren()

GeneratedMessage.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessage.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessage.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessage.Builder.getUnknownFieldSetBuilder()

GeneratedMessage.Builder.getUnknownFields()

GeneratedMessage.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessage.Builder.internalGetFieldAccessorTable()

GeneratedMessage.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessage.Builder.internalGetMapFieldReflection(int)

GeneratedMessage.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessage.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessage.Builder.isClean()

GeneratedMessage.Builder.isInitialized()

GeneratedMessage.Builder.markClean()

GeneratedMessage.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessage.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessage.Builder.mergeUnknownVarintField(int,int)

GeneratedMessage.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessage.Builder.onBuilt()

GeneratedMessage.Builder.onChanged()

com.google.protobuf.GeneratedMessage.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessage.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessage.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessage.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessage.Builder.setUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessage.Builder.setUnknownFieldsProto3(com.google.protobuf.UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

Methods

build()

public NluSettings build()

Returns
Type	Description
NluSettings

buildPartial()

public NluSettings buildPartial()

Returns
Type	Description
NluSettings

clear()

public NluSettings.Builder clear()

Returns
Type	Description
NluSettings.Builder

Overrides

GeneratedMessage.Builder<BuilderType>.clear()

clearClassificationThreshold()

public NluSettings.Builder clearClassificationThreshold()

To filter out false positive results and still get variety in matched natural language inputs for your agent, you can tune the machine learning classification threshold. If the returned score value is less than the threshold value, then a no-match event will be triggered. The score values range from 0.0 (completely uncertain) to 1.0 (completely certain). If set to 0.0, the default of 0.3 is used. You can set a separate classification threshold for the flow in each language enabled for the agent.

float classification_threshold = 3;

Returns
Type	Description
NluSettings.Builder	This builder for chaining.

clearModelTrainingMode()

public NluSettings.Builder clearModelTrainingMode()

Indicates NLU model training mode.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelTrainingMode model_training_mode = 4;

Returns
Type	Description
NluSettings.Builder	This builder for chaining.

clearModelType()

public NluSettings.Builder clearModelType()

Indicates the type of NLU model.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelType model_type = 1;

Returns
Type	Description
NluSettings.Builder	This builder for chaining.

getClassificationThreshold()

public float getClassificationThreshold()

To filter out false positive results and still get variety in matched natural language inputs for your agent, you can tune the machine learning classification threshold. If the returned score value is less than the threshold value, then a no-match event will be triggered. The score values range from 0.0 (completely uncertain) to 1.0 (completely certain). If set to 0.0, the default of 0.3 is used. You can set a separate classification threshold for the flow in each language enabled for the agent.

float classification_threshold = 3;

Returns
Type	Description
float	The classificationThreshold.

getDefaultInstanceForType()

public NluSettings getDefaultInstanceForType()

Returns
Type	Description
NluSettings

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessage.Builder<BuilderType>.getDescriptorForType()

getModelTrainingMode()

public NluSettings.ModelTrainingMode getModelTrainingMode()

Indicates NLU model training mode.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelTrainingMode model_training_mode = 4;

Returns
Type	Description
NluSettings.ModelTrainingMode	The modelTrainingMode.

getModelTrainingModeValue()

public int getModelTrainingModeValue()

Indicates NLU model training mode.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelTrainingMode model_training_mode = 4;

Returns
Type	Description
int	The enum numeric value on the wire for modelTrainingMode.

getModelType()

public NluSettings.ModelType getModelType()

Indicates the type of NLU model.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelType model_type = 1;

Returns
Type	Description
NluSettings.ModelType	The modelType.

getModelTypeValue()

public int getModelTypeValue()

Indicates the type of NLU model.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelType model_type = 1;

Returns
Type	Description
int	The enum numeric value on the wire for modelType.

internalGetFieldAccessorTable()

protected GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessage.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessage.Builder<BuilderType>.isInitialized()

mergeFrom(NluSettings other)

public NluSettings.Builder mergeFrom(NluSettings other)

Parameter
Name	Description
other	NluSettings

Returns
Type	Description
NluSettings.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public NluSettings.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
NluSettings.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public NluSettings.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
NluSettings.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

setClassificationThreshold(float value)

public NluSettings.Builder setClassificationThreshold(float value)

To filter out false positive results and still get variety in matched natural language inputs for your agent, you can tune the machine learning classification threshold. If the returned score value is less than the threshold value, then a no-match event will be triggered. The score values range from 0.0 (completely uncertain) to 1.0 (completely certain). If set to 0.0, the default of 0.3 is used. You can set a separate classification threshold for the flow in each language enabled for the agent.

float classification_threshold = 3;

Parameter
Name	Description
value	float The classificationThreshold to set.

Returns
Type	Description
NluSettings.Builder	This builder for chaining.

setModelTrainingMode(NluSettings.ModelTrainingMode value)

public NluSettings.Builder setModelTrainingMode(NluSettings.ModelTrainingMode value)

Indicates NLU model training mode.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelTrainingMode model_training_mode = 4;

Parameter
Name	Description
value	NluSettings.ModelTrainingMode The modelTrainingMode to set.

Returns
Type	Description
NluSettings.Builder	This builder for chaining.

setModelTrainingModeValue(int value)

public NluSettings.Builder setModelTrainingModeValue(int value)

Indicates NLU model training mode.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelTrainingMode model_training_mode = 4;

Parameter
Name	Description
value	int The enum numeric value on the wire for modelTrainingMode to set.

Returns
Type	Description
NluSettings.Builder	This builder for chaining.

setModelType(NluSettings.ModelType value)

public NluSettings.Builder setModelType(NluSettings.ModelType value)

Indicates the type of NLU model.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelType model_type = 1;

Parameter
Name	Description
value	NluSettings.ModelType The modelType to set.

Returns
Type	Description
NluSettings.Builder	This builder for chaining.

setModelTypeValue(int value)

public NluSettings.Builder setModelTypeValue(int value)

Indicates the type of NLU model.

.google.cloud.dialogflow.cx.v3beta1.NluSettings.ModelType model_type = 1;

Parameter
Name	Description
value	int The enum numeric value on the wire for modelType to set.

Returns
Type	Description
NluSettings.Builder	This builder for chaining.