Class TextSentimentAnnotation.Builder (2.3.10)

Stay organized with collections Save and categorize content based on your preferences.
public static final class TextSentimentAnnotation.Builder extends GeneratedMessageV3.Builder<TextSentimentAnnotation.Builder> implements TextSentimentAnnotationOrBuilder

Contains annotation details specific to text sentiment.

Protobuf type google.cloud.automl.v1.TextSentimentAnnotation

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TextSentimentAnnotation.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

build()

public TextSentimentAnnotation build()
Returns
TypeDescription
TextSentimentAnnotation

buildPartial()

public TextSentimentAnnotation buildPartial()
Returns
TypeDescription
TextSentimentAnnotation

clear()

public TextSentimentAnnotation.Builder clear()
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

clearField(Descriptors.FieldDescriptor field)

public TextSentimentAnnotation.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public TextSentimentAnnotation.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

clearSentiment()

public TextSentimentAnnotation.Builder clearSentiment()

Output only. The sentiment with the semantic, as given to the AutoMl.ImportData when populating the dataset from which the model used for the prediction had been trained. The sentiment values are between 0 and Dataset.text_sentiment_dataset_metadata.sentiment_max (inclusive), with higher value meaning more positive sentiment. They are completely relative, i.e. 0 means least positive sentiment and sentiment_max means the most positive from the sentiments present in the train data. Therefore e.g. if train data had only negative sentiment, then sentiment_max, would be still negative (although least negative). The sentiment shouldn't be confused with "score" or "magnitude" from the previous Natural Language Sentiment Analysis API.

int32 sentiment = 1;

Returns
TypeDescription
TextSentimentAnnotation.Builder

This builder for chaining.

clone()

public TextSentimentAnnotation.Builder clone()
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

getDefaultInstanceForType()

public TextSentimentAnnotation getDefaultInstanceForType()
Returns
TypeDescription
TextSentimentAnnotation

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getSentiment()

public int getSentiment()

Output only. The sentiment with the semantic, as given to the AutoMl.ImportData when populating the dataset from which the model used for the prediction had been trained. The sentiment values are between 0 and Dataset.text_sentiment_dataset_metadata.sentiment_max (inclusive), with higher value meaning more positive sentiment. They are completely relative, i.e. 0 means least positive sentiment and sentiment_max means the most positive from the sentiments present in the train data. Therefore e.g. if train data had only negative sentiment, then sentiment_max, would be still negative (although least negative). The sentiment shouldn't be confused with "score" or "magnitude" from the previous Natural Language Sentiment Analysis API.

int32 sentiment = 1;

Returns
TypeDescription
int

The sentiment.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(TextSentimentAnnotation other)

public TextSentimentAnnotation.Builder mergeFrom(TextSentimentAnnotation other)
Parameter
NameDescription
otherTextSentimentAnnotation
Returns
TypeDescription
TextSentimentAnnotation.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TextSentimentAnnotation.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public TextSentimentAnnotation.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TextSentimentAnnotation.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

setField(Descriptors.FieldDescriptor field, Object value)

public TextSentimentAnnotation.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public TextSentimentAnnotation.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides

setSentiment(int value)

public TextSentimentAnnotation.Builder setSentiment(int value)

Output only. The sentiment with the semantic, as given to the AutoMl.ImportData when populating the dataset from which the model used for the prediction had been trained. The sentiment values are between 0 and Dataset.text_sentiment_dataset_metadata.sentiment_max (inclusive), with higher value meaning more positive sentiment. They are completely relative, i.e. 0 means least positive sentiment and sentiment_max means the most positive from the sentiments present in the train data. Therefore e.g. if train data had only negative sentiment, then sentiment_max, would be still negative (although least negative). The sentiment shouldn't be confused with "score" or "magnitude" from the previous Natural Language Sentiment Analysis API.

int32 sentiment = 1;

Parameter
NameDescription
valueint

The sentiment to set.

Returns
TypeDescription
TextSentimentAnnotation.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final TextSentimentAnnotation.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TextSentimentAnnotation.Builder
Overrides