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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
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > TextSentimentAnnotation.BuilderImplements
TextSentimentAnnotationOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public TextSentimentAnnotation.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
TextSentimentAnnotation.Builder |
build()
public TextSentimentAnnotation build()
Type | Description |
TextSentimentAnnotation |
buildPartial()
public TextSentimentAnnotation buildPartial()
Type | Description |
TextSentimentAnnotation |
clear()
public TextSentimentAnnotation.Builder clear()
Type | Description |
TextSentimentAnnotation.Builder |
clearField(Descriptors.FieldDescriptor field)
public TextSentimentAnnotation.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
TextSentimentAnnotation.Builder |
clearOneof(Descriptors.OneofDescriptor oneof)
public TextSentimentAnnotation.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
TextSentimentAnnotation.Builder |
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;
Type | Description |
TextSentimentAnnotation.Builder | This builder for chaining. |
clone()
public TextSentimentAnnotation.Builder clone()
Type | Description |
TextSentimentAnnotation.Builder |
getDefaultInstanceForType()
public TextSentimentAnnotation getDefaultInstanceForType()
Type | Description |
TextSentimentAnnotation |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
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;
Type | Description |
int | The sentiment. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
mergeFrom(TextSentimentAnnotation other)
public TextSentimentAnnotation.Builder mergeFrom(TextSentimentAnnotation other)
Name | Description |
other | TextSentimentAnnotation |
Type | Description |
TextSentimentAnnotation.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public TextSentimentAnnotation.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
TextSentimentAnnotation.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public TextSentimentAnnotation.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
TextSentimentAnnotation.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final TextSentimentAnnotation.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
TextSentimentAnnotation.Builder |
setField(Descriptors.FieldDescriptor field, Object value)
public TextSentimentAnnotation.Builder setField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
TextSentimentAnnotation.Builder |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public TextSentimentAnnotation.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
TextSentimentAnnotation.Builder |
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;
Name | Description |
value | int The sentiment to set. |
Type | Description |
TextSentimentAnnotation.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final TextSentimentAnnotation.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
TextSentimentAnnotation.Builder |