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Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class EvaluatedAnnotation.
True positive, false positive, or false negative.
EvaluatedAnnotation is only available under ModelEvaluationSlice with slice
of annotationSpec
dimension.
Generated from protobuf message google.cloud.aiplatform.v1.EvaluatedAnnotation
Namespace
Google \ Cloud \ AIPlatform \ V1Methods
__construct
Constructor.
data
array
Optional. Data for populating the Message object.
↳ type
int
Output only. Type of the EvaluatedAnnotation.
↳ predictions
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 . 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
↳ ground_truths
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
↳ data_item_payload
Google\Protobuf\Value
Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.
↳ evaluated_data_item_view_id
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
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.
↳ error_analysis_annotations
array< Google\Cloud\AIPlatform\V1\ErrorAnalysisAnnotation
>
Annotations of model error analysis results.
getType
Output only. Type of the EvaluatedAnnotation.
int
setType
Output only. Type of the EvaluatedAnnotation.
var
int
$this
getPredictions
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 . 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
setPredictions
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 . 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
$this
getGroundTruths
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
setGroundTruths
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
$this
getDataItemPayload
Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.
hasDataItemPayload
clearDataItemPayload
setDataItemPayload
Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.
$this
getEvaluatedDataItemViewId
Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload .
string
setEvaluatedDataItemViewId
Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload .
var
string
$this
getExplanations
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.
setExplanations
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.
$this
getErrorAnalysisAnnotations
Annotations of model error analysis results.
setErrorAnalysisAnnotations
Annotations of model error analysis results.
$this
