kratos/third_party/google/cloud/automl/v1beta1/model_evaluation.proto

// Copyright 2018 Google LLC.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//

syntax = "proto3";

package google.cloud.automl.v1beta1;

import "google/api/annotations.proto";
import "google/cloud/automl/v1beta1/classification.proto";
import "google/cloud/automl/v1beta1/detection.proto";
import "google/cloud/automl/v1beta1/regression.proto";
import "google/cloud/automl/v1beta1/tables.proto";
import "google/cloud/automl/v1beta1/text_extraction.proto";
import "google/cloud/automl/v1beta1/text_sentiment.proto";
import "google/cloud/automl/v1beta1/translation.proto";
import "google/protobuf/timestamp.proto";

option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
option java_multiple_files = true;
option java_package = "com.google.cloud.automl.v1beta1";
option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1";


// Evaluation results of a model.
message ModelEvaluation {
  // Output only. Problem type specific evaluation metrics.
  oneof metrics {
    // Model evaluation metrics for image, text, video and tables
    // classification.
    // Tables problem is considered a classification when the target column
    // has either CATEGORY or ARRAY(CATEGORY) DataType.
    ClassificationEvaluationMetrics classification_evaluation_metrics = 8;

    // Model evaluation metrics for Tables regression.
    // Tables problem is considered a regression when the target column
    // has FLOAT64 DataType.
    RegressionEvaluationMetrics regression_evaluation_metrics = 24;

    // Model evaluation metrics for translation.
    TranslationEvaluationMetrics translation_evaluation_metrics = 9;

    // Model evaluation metrics for image object detection.
    ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;

    // Evaluation metrics for text sentiment models.
    TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;

    // Evaluation metrics for text extraction models.
    TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;
  }

  // Output only.
  // Resource name of the model evaluation.
  // Format:
  //
  // `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}`
  string name = 1;

  // Output only.
  // The ID of the annotation spec that the model evaluation applies to. The
  // The ID is empty for the overall model evaluation.
  // For Tables classification these are the distinct values of the target
  // column at the moment of the evaluation; for this problem annotation specs
  // in the dataset do not exist.
  // NOTE: Currently there is no way to obtain the display_name of the
  // annotation spec from its ID. To see the display_names, review the model
  // evaluations in the UI.
  string annotation_spec_id = 2;

  // Output only. The value of [AnnotationSpec.display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] when the model
  // was trained. Because this field returns a value at model training time,
  // for different models trained using the same dataset, the returned value
  // could be different as model owner could update the display_name between
  // any two model training.
  // The display_name is empty for the overall model evaluation.
  string display_name = 15;

  // Output only.
  // Timestamp when this model evaluation was created.
  google.protobuf.Timestamp create_time = 5;

  // Output only.
  // The number of examples used for model evaluation, i.e. for
  // which ground truth from time of model creation is compared against the
  // predicted annotations created by the model.
  // For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is
  // the total number of all examples used for evaluation.
  // Otherwise, this is the count of examples that according to the ground
  // truth were annotated by the
  //
  // [annotation_spec_id][google.cloud.automl.v1beta1.ModelEvaluation.annotation_spec_id].
  int32 evaluated_example_count = 6;
}