- 2.55.0 (latest)
- 2.54.0
- 2.53.0
- 2.52.0
- 2.51.0
- 2.49.0
- 2.48.0
- 2.47.0
- 2.46.0
- 2.45.0
- 2.44.0
- 2.43.0
- 2.42.0
- 2.41.0
- 2.40.0
- 2.39.0
- 2.37.0
- 2.36.0
- 2.35.0
- 2.34.0
- 2.33.0
- 2.32.0
- 2.31.0
- 2.30.0
- 2.29.0
- 2.28.0
- 2.27.0
- 2.24.0
- 2.23.0
- 2.22.0
- 2.21.0
- 2.20.0
- 2.19.0
- 2.18.0
- 2.17.0
- 2.16.0
- 2.15.0
- 2.14.0
- 2.13.0
- 2.12.0
- 2.11.0
- 2.10.0
- 2.9.0
- 2.8.0
- 2.7.0
- 2.6.0
- 2.5.0
- 2.4.0
- 2.3.18
- 2.2.3
- 2.1.23
public static final class TextSentimentProto.TextSentimentAnnotation.Builder extends GeneratedMessageV3.Builder<TextSentimentProto.TextSentimentAnnotation.Builder> implements TextSentimentProto.TextSentimentAnnotationOrBuilderContains annotation details specific to text sentiment.
Protobuf type google.cloud.automl.v1beta1.TextSentimentAnnotation
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > TextSentimentProto.TextSentimentAnnotation.BuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor | |
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public TextSentimentProto.TextSentimentAnnotation.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field | FieldDescriptor |
value | Object |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
build()
public TextSentimentProto.TextSentimentAnnotation build()| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation | |
buildPartial()
public TextSentimentProto.TextSentimentAnnotation buildPartial()| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation | |
clear()
public TextSentimentProto.TextSentimentAnnotation.Builder clear()| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
clearField(Descriptors.FieldDescriptor field)
public TextSentimentProto.TextSentimentAnnotation.Builder clearField(Descriptors.FieldDescriptor field)| Parameter | |
|---|---|
| Name | Description |
field | FieldDescriptor |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
clearOneof(Descriptors.OneofDescriptor oneof)
public TextSentimentProto.TextSentimentAnnotation.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof | OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
clearSentiment()
public TextSentimentProto.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 | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | This builder for chaining. |
clone()
public TextSentimentProto.TextSentimentAnnotation.Builder clone()| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
getDefaultInstanceForType()
public TextSentimentProto.TextSentimentAnnotation getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation | |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor | |
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 | |
|---|---|
| Type | Description |
int | The sentiment. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable | |
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean | |
mergeFrom(TextSentimentProto.TextSentimentAnnotation other)
public TextSentimentProto.TextSentimentAnnotation.Builder mergeFrom(TextSentimentProto.TextSentimentAnnotation other)| Parameter | |
|---|---|
| Name | Description |
other | TextSentimentProto.TextSentimentAnnotation |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public TextSentimentProto.TextSentimentAnnotation.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
| Exceptions | |
|---|---|
| Type | Description |
IOException | |
mergeFrom(Message other)
public TextSentimentProto.TextSentimentAnnotation.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other | Message |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final TextSentimentProto.TextSentimentAnnotation.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields | UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
setField(Descriptors.FieldDescriptor field, Object value)
public TextSentimentProto.TextSentimentAnnotation.Builder setField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field | FieldDescriptor |
value | Object |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public TextSentimentProto.TextSentimentAnnotation.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)| Parameters | |
|---|---|
| Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |
setSentiment(int value)
public TextSentimentProto.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 | |
|---|---|
| Name | Description |
value | intThe sentiment to set. |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final TextSentimentProto.TextSentimentAnnotation.Builder setUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields | UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
TextSentimentProto.TextSentimentAnnotation.Builder | |