Send feedback
Class TextSentimentProto.TextSentimentAnnotation (2.35.0)
Stay organized with collections
Save and categorize content based on your preferences.
Version 2.35.0 keyboard_arrow_down
public static final class TextSentimentProto . TextSentimentAnnotation extends GeneratedMessageV3 implements TextSentimentProto . TextSentimentAnnotationOrBuilder
Contains annotation details specific to text sentiment.
Protobuf type google.cloud.automl.v1beta1.TextSentimentAnnotation
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
Static Fields
SENTIMENT_FIELD_NUMBER
public static final int SENTIMENT_FIELD_NUMBER
Field Value Type Description int
Static Methods
getDefaultInstance()
public static TextSentimentProto . TextSentimentAnnotation getDefaultInstance ()
getDescriptor()
public static final Descriptors . Descriptor getDescriptor ()
newBuilder()
public static TextSentimentProto . TextSentimentAnnotation . Builder newBuilder ()
newBuilder(TextSentimentProto.TextSentimentAnnotation prototype)
public static TextSentimentProto . TextSentimentAnnotation . Builder newBuilder ( TextSentimentProto . TextSentimentAnnotation prototype )
parseDelimitedFrom(InputStream input)
public static TextSentimentProto . TextSentimentAnnotation parseDelimitedFrom ( InputStream input )
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static TextSentimentProto . TextSentimentAnnotation parseDelimitedFrom ( InputStream input , ExtensionRegistryLite extensionRegistry )
parseFrom(byte[] data)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( byte [] data )
Parameter Name Description databyte []
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( byte [] data , ExtensionRegistryLite extensionRegistry )
parseFrom(ByteString data)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( ByteString data )
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( ByteString data , ExtensionRegistryLite extensionRegistry )
parseFrom(CodedInputStream input)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( CodedInputStream input )
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( CodedInputStream input , ExtensionRegistryLite extensionRegistry )
parseFrom(InputStream input)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( InputStream input )
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( InputStream input , ExtensionRegistryLite extensionRegistry )
parseFrom(ByteBuffer data)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( ByteBuffer data )
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static TextSentimentProto . TextSentimentAnnotation parseFrom ( ByteBuffer data , ExtensionRegistryLite extensionRegistry )
parser()
public static Parser<TextSentimentProto . TextSentimentAnnotation> parser ()
Methods
equals(Object obj)
public boolean equals ( Object obj )
Parameter Name Description objObject
Overrides
getDefaultInstanceForType()
public TextSentimentProto . TextSentimentAnnotation getDefaultInstanceForType ()
getParserForType()
public Parser<TextSentimentProto . TextSentimentAnnotation> getParserForType ()
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 Type Description int The sentiment.
getSerializedSize()
public int getSerializedSize ()
Returns Type Description int
Overrides
hashCode()
Returns Type Description int
Overrides
internalGetFieldAccessorTable()
protected GeneratedMessageV3 . FieldAccessorTable internalGetFieldAccessorTable ()
Overrides
isInitialized()
public final boolean isInitialized ()
Overrides
newBuilderForType()
public TextSentimentProto . TextSentimentAnnotation . Builder newBuilderForType ()
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected TextSentimentProto . TextSentimentAnnotation . Builder newBuilderForType ( GeneratedMessageV3 . BuilderParent parent )
Overrides
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance ( GeneratedMessageV3 . UnusedPrivateParameter unused )
Overrides
toBuilder()
public TextSentimentProto . TextSentimentAnnotation . Builder toBuilder ()
writeTo(CodedOutputStream output)
public void writeTo ( CodedOutputStream output )
Overrides
Send feedback
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2024-10-04 UTC.
[{
"type": "thumb-down",
"id": "hardToUnderstand",
"label":"Hard to understand"
},{
"type": "thumb-down",
"id": "incorrectInformationOrSampleCode",
"label":"Incorrect information or sample code"
},{
"type": "thumb-down",
"id": "missingTheInformationSamplesINeed",
"label":"Missing the information/samples I need"
},{
"type": "thumb-down",
"id": "otherDown",
"label":"Other"
}]
[{
"type": "thumb-up",
"id": "easyToUnderstand",
"label":"Easy to understand"
},{
"type": "thumb-up",
"id": "solvedMyProblem",
"label":"Solved my problem"
},{
"type": "thumb-up",
"id": "otherUp",
"label":"Other"
}]
Need to tell us more?
{"lastModified": "Last updated 2024-10-04 UTC."}
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-10-04 UTC."]]
