max_bounding_box_count
: (int64) The maximum number of bounding boxes to return per image.
AutoML Natural Language Sentiment Analysis
sentiment_score
: (float, deprecated) A value between -1 and 1,
-1 maps to least positive sentiment, while 1 maps to the most positive
one and the higher the score, the more positive the sentiment in the
document is. Yet these values are relative to the training data, so
e.g. if all data was positive then -1 is also positive (though
the least).
sentiment_score is not the same as "score" and "magnitude"
from Sentiment Analysis in the Natural Language API.
value (::Google::Protobuf::Map{::String => ::String}) — Additional domain-specific prediction response metadata.
AutoML Vision Object Detection
max_bounding_box_count
: (int64) The maximum number of bounding boxes to return per image.
AutoML Natural Language Sentiment Analysis
sentiment_score
: (float, deprecated) A value between -1 and 1,
-1 maps to least positive sentiment, while 1 maps to the most positive
one and the higher the score, the more positive the sentiment in the
document is. Yet these values are relative to the training data, so
e.g. if all data was positive then -1 is also positive (though
the least).
sentiment_score is not the same as "score" and "magnitude"
from Sentiment Analysis in the Natural Language API.
max_bounding_box_count
: (int64) The maximum number of bounding boxes to return per image.
AutoML Natural Language Sentiment Analysis
sentiment_score
: (float, deprecated) A value between -1 and 1,
-1 maps to least positive sentiment, while 1 maps to the most positive
one and the higher the score, the more positive the sentiment in the
document is. Yet these values are relative to the training data, so
e.g. if all data was positive then -1 is also positive (though
the least).
sentiment_score is not the same as "score" and "magnitude"
from Sentiment Analysis in the Natural Language API.
For AutoML Natural Language (Classification, Entity Extraction, and
Sentiment Analysis), if the input is a document, the recognized text is
returned in the
document_text
property.
value (::Google::Cloud::AutoML::V1::ExamplePayload) — The preprocessed example that AutoML actually makes prediction on.
Empty if AutoML does not preprocess the input example.
For AutoML Natural Language (Classification, Entity Extraction, and
Sentiment Analysis), if the input is a document, the recognized text is
returned in the
document_text
property.
For AutoML Natural Language (Classification, Entity Extraction, and
Sentiment Analysis), if the input is a document, the recognized text is
returned in the
document_text
property.
[[["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 2025-08-28 UTC."],[],[],null,["# Cloud AutoML V1 API - Class Google::Cloud::AutoML::V1::PredictResponse (v1.3.1)\n\nVersion latestkeyboard_arrow_down\n\n- [1.3.1 (latest)](/ruby/docs/reference/google-cloud-automl-v1/latest/Google-Cloud-AutoML-V1-PredictResponse)\n- [1.3.0](/ruby/docs/reference/google-cloud-automl-v1/1.3.0/Google-Cloud-AutoML-V1-PredictResponse)\n- [1.2.1](/ruby/docs/reference/google-cloud-automl-v1/1.2.1/Google-Cloud-AutoML-V1-PredictResponse)\n- [1.1.0](/ruby/docs/reference/google-cloud-automl-v1/1.1.0/Google-Cloud-AutoML-V1-PredictResponse)\n- [1.0.1](/ruby/docs/reference/google-cloud-automl-v1/1.0.1/Google-Cloud-AutoML-V1-PredictResponse)\n- [0.10.0](/ruby/docs/reference/google-cloud-automl-v1/0.10.0/Google-Cloud-AutoML-V1-PredictResponse)\n- [0.9.2](/ruby/docs/reference/google-cloud-automl-v1/0.9.2/Google-Cloud-AutoML-V1-PredictResponse)\n- [0.8.0](/ruby/docs/reference/google-cloud-automl-v1/0.8.0/Google-Cloud-AutoML-V1-PredictResponse)\n- [0.7.0](/ruby/docs/reference/google-cloud-automl-v1/0.7.0/Google-Cloud-AutoML-V1-PredictResponse)\n- [0.6.0](/ruby/docs/reference/google-cloud-automl-v1/0.6.0/Google-Cloud-AutoML-V1-PredictResponse)\n- [0.5.1](/ruby/docs/reference/google-cloud-automl-v1/0.5.1/Google-Cloud-AutoML-V1-PredictResponse)\n- [0.4.8](/ruby/docs/reference/google-cloud-automl-v1/0.4.8/Google-Cloud-AutoML-V1-PredictResponse) \nReference documentation and code samples for the Cloud AutoML V1 API class Google::Cloud::AutoML::V1::PredictResponse.\n\nResponse message for [PredictionService.Predict](/ruby/docs/reference/google-cloud-automl-v1/latest/Google-Cloud-AutoML-V1-PredictionService-Client#Google__Cloud__AutoML__V1__PredictionService__Client_predict_instance_ \"Google::Cloud::AutoML::V1::PredictionService::Client#predict (method)\"). \n\nInherits\n--------\n\n- Object \n\nExtended By\n-----------\n\n- Google::Protobuf::MessageExts::ClassMethods \n\nIncludes\n--------\n\n- Google::Protobuf::MessageExts\n\nMethods\n-------\n\n### #metadata\n\n def metadata() -\u003e ::Google::Protobuf::Map{::String =\u003e ::String}\n\n**Returns**\n\n- (::Google::Protobuf::Map{::String =\\\u003e ::String}) --- Additional domain-specific prediction response metadata.\n\n AutoML Vision Object Detection\n\n `max_bounding_box_count`\n : (int64) The maximum number of bounding boxes to return per image.\n\n AutoML Natural Language Sentiment Analysis\n\n `sentiment_score`\n : (float, deprecated) A value between -1 and 1,\n -1 maps to least positive sentiment, while 1 maps to the most positive\n one and the higher the score, the more positive the sentiment in the\n document is. Yet these values are relative to the training data, so\n e.g. if all data was positive then -1 is also positive (though\n the least).\n `sentiment_score` is not the same as \"score\" and \"magnitude\"\n from Sentiment Analysis in the Natural Language API.\n\n### #metadata=\n\n def metadata=(value) -\u003e ::Google::Protobuf::Map{::String =\u003e ::String}\n\n**Parameter**\n\n- **value** (::Google::Protobuf::Map{::String =\\\u003e ::String}) --- Additional domain-specific prediction response metadata.\n\n\n AutoML Vision Object Detection\n\n `max_bounding_box_count`\n : (int64) The maximum number of bounding boxes to return per image.\n\n AutoML Natural Language Sentiment Analysis\n\n `sentiment_score`\n : (float, deprecated) A value between -1 and 1,\n -1 maps to least positive sentiment, while 1 maps to the most positive\n one and the higher the score, the more positive the sentiment in the\n document is. Yet these values are relative to the training data, so\n e.g. if all data was positive then -1 is also positive (though\n the least).\n `sentiment_score` is not the same as \"score\" and \"magnitude\"\nfrom Sentiment Analysis in the Natural Language API. \n**Returns**\n\n- (::Google::Protobuf::Map{::String =\\\u003e ::String}) --- Additional domain-specific prediction response metadata.\n\n AutoML Vision Object Detection\n\n `max_bounding_box_count`\n : (int64) The maximum number of bounding boxes to return per image.\n\n AutoML Natural Language Sentiment Analysis\n\n `sentiment_score`\n : (float, deprecated) A value between -1 and 1,\n -1 maps to least positive sentiment, while 1 maps to the most positive\n one and the higher the score, the more positive the sentiment in the\n document is. Yet these values are relative to the training data, so\n e.g. if all data was positive then -1 is also positive (though\n the least).\n `sentiment_score` is not the same as \"score\" and \"magnitude\"\n from Sentiment Analysis in the Natural Language API.\n\n### #payload\n\n def payload() -\u003e ::Array\u003c::Google::Cloud::AutoML::V1::AnnotationPayload\u003e\n\n**Returns**\n\n- (::Array\\\u003c[::Google::Cloud::AutoML::V1::AnnotationPayload](./Google-Cloud-AutoML-V1-AnnotationPayload)\\\u003e) --- Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload.\n\n### #payload=\n\n def payload=(value) -\u003e ::Array\u003c::Google::Cloud::AutoML::V1::AnnotationPayload\u003e\n\n**Parameter**\n\n- **value** (::Array\\\u003c[::Google::Cloud::AutoML::V1::AnnotationPayload](./Google-Cloud-AutoML-V1-AnnotationPayload)\\\u003e) --- Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload. \n**Returns**\n\n- (::Array\\\u003c[::Google::Cloud::AutoML::V1::AnnotationPayload](./Google-Cloud-AutoML-V1-AnnotationPayload)\\\u003e) --- Prediction result. AutoML Translation and AutoML Natural Language Sentiment Analysis return precisely one payload.\n\n### #preprocessed_input\n\n def preprocessed_input() -\u003e ::Google::Cloud::AutoML::V1::ExamplePayload\n\n**Returns**\n\n- ([::Google::Cloud::AutoML::V1::ExamplePayload](./Google-Cloud-AutoML-V1-ExamplePayload)) --- The preprocessed example that AutoML actually makes prediction on. Empty if AutoML does not preprocess the input example.\n\n\n For AutoML Natural Language (Classification, Entity Extraction, and\n Sentiment Analysis), if the input is a document, the recognized text is\n returned in the\n [document_text](/ruby/docs/reference/google-cloud-automl-v1/latest/Google-Cloud-AutoML-V1-Document#Google__Cloud__AutoML__V1__Document_document_text_instance_ \"Google::Cloud::AutoML::V1::Document#document_text (method)\")\n property.\n\n### #preprocessed_input=\n\n def preprocessed_input=(value) -\u003e ::Google::Cloud::AutoML::V1::ExamplePayload\n\n**Parameter**\n\n- **value** ([::Google::Cloud::AutoML::V1::ExamplePayload](./Google-Cloud-AutoML-V1-ExamplePayload)) --- The preprocessed example that AutoML actually makes prediction on. Empty if AutoML does not preprocess the input example.\n\n\n For AutoML Natural Language (Classification, Entity Extraction, and\n Sentiment Analysis), if the input is a document, the recognized text is\n returned in the\n [document_text](/ruby/docs/reference/google-cloud-automl-v1/latest/Google-Cloud-AutoML-V1-Document#Google__Cloud__AutoML__V1__Document_document_text_instance_ \"Google::Cloud::AutoML::V1::Document#document_text (method)\")\nproperty. \n**Returns**\n\n- ([::Google::Cloud::AutoML::V1::ExamplePayload](./Google-Cloud-AutoML-V1-ExamplePayload)) --- The preprocessed example that AutoML actually makes prediction on. Empty if AutoML does not preprocess the input example.\n\n\n For AutoML Natural Language (Classification, Entity Extraction, and\n Sentiment Analysis), if the input is a document, the recognized text is\n returned in the\n [document_text](/ruby/docs/reference/google-cloud-automl-v1/latest/Google-Cloud-AutoML-V1-Document#Google__Cloud__AutoML__V1__Document_document_text_instance_ \"Google::Cloud::AutoML::V1::Document#document_text (method)\")\n property."]]
