Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::EvaluatedAnnotation (v0.24.0)

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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::EvaluatedAnnotation.

True positive, false positive, or false negative.

EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of annotationSpec dimension.

Inherits

• Object

Extended By

• Google::Protobuf::MessageExts::ClassMethods

Includes

• Google::Protobuf::MessageExts

Methods

#data_item_payload

def data_item_payload() -> ::Google::Protobuf::Value

Returns

• (::Google::Protobuf::Value) — Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.

#error_analysis_annotations

def error_analysis_annotations() -> ::Array<::Google::Cloud::AIPlatform::V1::ErrorAnalysisAnnotation>

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::ErrorAnalysisAnnotation>) — Annotations of model error analysis results.

#error_analysis_annotations=

def error_analysis_annotations=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::ErrorAnalysisAnnotation>

Parameter

• value (::Array<::Google::Cloud::AIPlatform::V1::ErrorAnalysisAnnotation>) — Annotations of model error analysis results.

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::ErrorAnalysisAnnotation>) — Annotations of model error analysis results.

#evaluated_data_item_view_id

def evaluated_data_item_view_id() -> ::String

Returns

• (::String) — Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload.

#explanations

def explanations() -> ::Array<::Google::Cloud::AIPlatform::V1::EvaluatedAnnotationExplanation>

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::EvaluatedAnnotationExplanation>) — Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method.

  The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list.

#explanations=

def explanations=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::EvaluatedAnnotationExplanation>

Parameter

• value (::Array<::Google::Cloud::AIPlatform::V1::EvaluatedAnnotationExplanation>) — Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method.

  The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list.

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::EvaluatedAnnotationExplanation>) — Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method.

  The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list.

#ground_truths

def ground_truths() -> ::Array<::Google::Protobuf::Value>

Returns

• (::Array<::Google::Protobuf::Value>) — Output only. The ground truth Annotations, i.e. the Annotations that exist in the test data the Model is evaluated on.

  For true positive, there is one and only one ground truth annotation, which matches the only prediction in predictions.

  For false positive, there are zero or more ground truth annotations that are similar to the only prediction in predictions, but not enough for a match.

  For false negative, there is one and only one ground truth annotation, which doesn't match any predictions created by the model.

  The schema of the ground truth is stored in ModelEvaluation.annotation_schema_uri

#predictions

def predictions() -> ::Array<::Google::Protobuf::Value>

Returns

• (::Array<::Google::Protobuf::Value>) — Output only. The model predicted annotations.

  For true positive, there is one and only one prediction, which matches the only one ground truth annotation in ground_truths.

  For false positive, there is one and only one prediction, which doesn't match any ground truth annotation of the corresponding [data_item_view_id][EvaluatedAnnotation.data_item_view_id].

  For false negative, there are zero or more predictions which are similar to the only ground truth annotation in ground_truths but not enough for a match.

  The schema of the prediction is stored in ModelEvaluation.annotation_schema_uri

#type

def type() -> ::Google::Cloud::AIPlatform::V1::EvaluatedAnnotation::EvaluatedAnnotationType

Returns

• (::Google::Cloud::AIPlatform::V1::EvaluatedAnnotation::EvaluatedAnnotationType) — Output only. Type of the EvaluatedAnnotation.