proto_docs/google/cloud/automl/v1beta1/classification.rb in google-cloud-automl-v1beta1-0.1.0 vs proto_docs/google/cloud/automl/v1beta1/classification.rb in google-cloud-automl-v1beta1-0.1.1

- old
+ new

@@ -21,24 +21,24 @@ module Cloud module AutoML module V1beta1 # Contains annotation details specific to classification. # @!attribute [rw] score - # @return [Float] + # @return [::Float] # Output only. A confidence estimate between 0.0 and 1.0. A higher value # means greater confidence that the annotation is positive. If a user # approves an annotation as negative or positive, the score value remains # unchanged. If a user creates an annotation, the score is 0 for negative or # 1 for positive. class ClassificationAnnotation - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # Contains annotation details specific to video classification. # @!attribute [rw] type - # @return [String] + # @return [::String] # Output only. Expresses the type of video classification. Possible values: # # * `segment` - Classification done on a specified by user # time segment of a video. AnnotationSpec is answered to be present # in that time segment, if it is present in any part of it. The video @@ -59,161 +59,161 @@ # that user specified in the request configuration. # WARNING: Model evaluation is not done for this classification type, # the quality of it depends on training data, but there are no # metrics provided to describe that quality. # @!attribute [rw] classification_annotation - # @return [Google::Cloud::AutoML::V1beta1::ClassificationAnnotation] + # @return [::Google::Cloud::AutoML::V1beta1::ClassificationAnnotation] # Output only . The classification details of this annotation. # @!attribute [rw] time_segment - # @return [Google::Cloud::AutoML::V1beta1::TimeSegment] + # @return [::Google::Cloud::AutoML::V1beta1::TimeSegment] # Output only . The time segment of the video to which the # annotation applies. class VideoClassificationAnnotation - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # Model evaluation metrics for classification problems. # Note: For Video Classification this metrics only describe quality of the # Video Classification predictions of "segment_classification" type. # @!attribute [rw] au_prc - # @return [Float] + # @return [::Float] # Output only. The Area Under Precision-Recall Curve metric. Micro-averaged # for the overall evaluation. # @!attribute [rw] base_au_prc - # @return [Float] + # @return [::Float] # Output only. The Area Under Precision-Recall Curve metric based on priors. # Micro-averaged for the overall evaluation. # Deprecated. # @!attribute [rw] au_roc - # @return [Float] + # @return [::Float] # Output only. The Area Under Receiver Operating Characteristic curve metric. # Micro-averaged for the overall evaluation. # @!attribute [rw] log_loss - # @return [Float] + # @return [::Float] # Output only. The Log Loss metric. # @!attribute [rw] confidence_metrics_entry - # @return [Array<Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfidenceMetricsEntry>] + # @return [::Array<::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfidenceMetricsEntry>] # Output only. Metrics for each confidence_threshold in # 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and # position_threshold = INT32_MAX_VALUE. # ROC and precision-recall curves, and other aggregated metrics are derived # from them. The confidence metrics entries may also be supplied for # additional values of position_threshold, but from these no aggregated # metrics are computed. # @!attribute [rw] confusion_matrix - # @return [Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix] + # @return [::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix] # Output only. Confusion matrix of the evaluation. # Only set for MULTICLASS classification problems where number # of labels is no more than 10. # Only set for model level evaluation, not for evaluation per label. # @!attribute [rw] annotation_spec_id - # @return [Array<String>] + # @return [::Array<::String>] # Output only. The annotation spec ids used for this evaluation. class ClassificationEvaluationMetrics - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods # Metrics for a single confidence threshold. # @!attribute [rw] confidence_threshold - # @return [Float] + # @return [::Float] # Output only. Metrics are computed with an assumption that the model # never returns predictions with score lower than this value. # @!attribute [rw] position_threshold - # @return [Integer] + # @return [::Integer] # Output only. Metrics are computed with an assumption that the model # always returns at most this many predictions (ordered by their score, # descendingly), but they all still need to meet the confidence_threshold. # @!attribute [rw] recall - # @return [Float] + # @return [::Float] # Output only. Recall (True Positive Rate) for the given confidence # threshold. # @!attribute [rw] precision - # @return [Float] + # @return [::Float] # Output only. Precision for the given confidence threshold. # @!attribute [rw] false_positive_rate - # @return [Float] + # @return [::Float] # Output only. False Positive Rate for the given confidence threshold. # @!attribute [rw] f1_score - # @return [Float] + # @return [::Float] # Output only. The harmonic mean of recall and precision. # @!attribute [rw] recall_at1 - # @return [Float] + # @return [::Float] # Output only. The Recall (True Positive Rate) when only considering the # label that has the highest prediction score and not below the confidence # threshold for each example. # @!attribute [rw] precision_at1 - # @return [Float] + # @return [::Float] # Output only. The precision when only considering the label that has the # highest prediction score and not below the confidence threshold for each # example. # @!attribute [rw] false_positive_rate_at1 - # @return [Float] + # @return [::Float] # Output only. The False Positive Rate when only considering the label that # has the highest prediction score and not below the confidence threshold # for each example. # @!attribute [rw] f1_score_at1 - # @return [Float] - # Output only. The harmonic mean of {Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfidenceMetricsEntry#recall_at1 recall_at1} and {Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfidenceMetricsEntry#precision_at1 precision_at1}. + # @return [::Float] + # Output only. The harmonic mean of {::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfidenceMetricsEntry#recall_at1 recall_at1} and {::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfidenceMetricsEntry#precision_at1 precision_at1}. # @!attribute [rw] true_positive_count - # @return [Integer] + # @return [::Integer] # Output only. The number of model created labels that match a ground truth # label. # @!attribute [rw] false_positive_count - # @return [Integer] + # @return [::Integer] # Output only. The number of model created labels that do not match a # ground truth label. # @!attribute [rw] false_negative_count - # @return [Integer] + # @return [::Integer] # Output only. The number of ground truth labels that are not matched # by a model created label. # @!attribute [rw] true_negative_count - # @return [Integer] + # @return [::Integer] # Output only. The number of labels that were not created by the model, # but if they would, they would not match a ground truth label. class ConfidenceMetricsEntry - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # Confusion matrix of the model running the classification. # @!attribute [rw] annotation_spec_id - # @return [Array<String>] + # @return [::Array<::String>] # Output only. IDs of the annotation specs used in the confusion matrix. # For Tables CLASSIFICATION # # [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] # only list of [annotation_spec_display_name-s][] is populated. # @!attribute [rw] display_name - # @return [Array<String>] + # @return [::Array<::String>] # Output only. Display name of the annotation specs used in the confusion # matrix, as they were at the moment of the evaluation. For Tables # CLASSIFICATION # # [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type], # distinct values of the target column at the moment of the model # evaluation are populated here. # @!attribute [rw] row - # @return [Array<Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::Row>] + # @return [::Array<::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::Row>] # Output only. Rows in the confusion matrix. The number of rows is equal to # the size of `annotation_spec_id`. # `row[i].example_count[j]` is the number of examples that have ground # truth of the `annotation_spec_id[i]` and are predicted as # `annotation_spec_id[j]` by the model being evaluated. class ConfusionMatrix - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods # Output only. A row in the confusion matrix. # @!attribute [rw] example_count - # @return [Array<Integer>] + # @return [::Array<::Integer>] # Output only. Value of the specific cell in the confusion matrix. # The number of values each row has (i.e. the length of the row) is equal # to the length of the `annotation_spec_id` field or, if that one is not - # populated, length of the {Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix#display_name display_name} field. + # populated, length of the {::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix#display_name display_name} field. class Row - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end end end # Type of the classification problem.