// Copyright 2019 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
//
// https://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.
// Note: this file is purely for documentation. Any contents are not expected
// to be loaded as the JS file.
/**
* Evaluation results of a model.
*
* @property {Object} classificationEvaluationMetrics
* Model evaluation metrics for image, text, video and tables
* classification.
* Tables problem is considered a classification when the target column
* is CATEGORY DataType.
*
* This object should have the same structure as [ClassificationEvaluationMetrics]{@link google.cloud.automl.v1beta1.ClassificationEvaluationMetrics}
*
* @property {Object} regressionEvaluationMetrics
* Model evaluation metrics for Tables regression.
* Tables problem is considered a regression when the target column
* has FLOAT64 DataType.
*
* This object should have the same structure as [RegressionEvaluationMetrics]{@link google.cloud.automl.v1beta1.RegressionEvaluationMetrics}
*
* @property {Object} translationEvaluationMetrics
* Model evaluation metrics for translation.
*
* This object should have the same structure as [TranslationEvaluationMetrics]{@link google.cloud.automl.v1beta1.TranslationEvaluationMetrics}
*
* @property {Object} imageObjectDetectionEvaluationMetrics
* Model evaluation metrics for image object detection.
*
* This object should have the same structure as [ImageObjectDetectionEvaluationMetrics]{@link google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics}
*
* @property {Object} videoObjectTrackingEvaluationMetrics
* Model evaluation metrics for video object tracking.
*
* This object should have the same structure as [VideoObjectTrackingEvaluationMetrics]{@link google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetrics}
*
* @property {Object} textSentimentEvaluationMetrics
* Evaluation metrics for text sentiment models.
*
* This object should have the same structure as [TextSentimentEvaluationMetrics]{@link google.cloud.automl.v1beta1.TextSentimentEvaluationMetrics}
*
* @property {Object} textExtractionEvaluationMetrics
* Evaluation metrics for text extraction models.
*
* This object should have the same structure as [TextExtractionEvaluationMetrics]{@link google.cloud.automl.v1beta1.TextExtractionEvaluationMetrics}
*
* @property {string} name
* Output only. Resource name of the model evaluation.
* Format:
*
* `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}`
*
* @property {string} annotationSpecId
* 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 annotation specs in the dataset do not exist and this ID is
* always not set, but for CLASSIFICATION
*
* prediction_type-s
* the
* display_name
* field is used.
*
* @property {string} displayName
* Output only. The value of
* display_name at
* the moment when the model was trained. Because this field returns a value
* at model training time, for different models trained from the same dataset,
* the values may differ, since display names could had been changed between
* the two model's trainings.
* For Tables CLASSIFICATION
*
* prediction_type-s
* distinct values of the target column at the moment of the model evaluation
* are populated here.
* The display_name is empty for the overall model evaluation.
*
* @property {Object} createTime
* Output only. Timestamp when this model evaluation was created.
*
* This object should have the same structure as [Timestamp]{@link google.protobuf.Timestamp}
*
* @property {number} evaluatedExampleCount
* 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.
*
* @typedef ModelEvaluation
* @memberof google.cloud.automl.v1beta1
* @see [google.cloud.automl.v1beta1.ModelEvaluation definition in proto format]{@link https://github.com/googleapis/googleapis/blob/master/google/cloud/automl/v1beta1/model_evaluation.proto}
*/
const ModelEvaluation = {
// This is for documentation. Actual contents will be loaded by gRPC.
};