Module gapi_grpc::google::cloud::bigquery::v2::model

Modules

arima_forecasting_metrics
binary_classification_metrics
clustering_metrics
evaluation_metrics
global_explanation
kmeans_enums
multi_class_classification_metrics
seasonal_period
training_run

Structs

AggregateClassificationMetrics	Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows.
ArimaFittingMetrics	ARIMA model fitting metrics.
ArimaForecastingMetrics	Model evaluation metrics for ARIMA forecasting models.
ArimaOrder	Arima order, can be used for both non-seasonal and seasonal parts.
BinaryClassificationMetrics	Evaluation metrics for binary classification/classifier models.
ClusteringMetrics	Evaluation metrics for clustering models.
DataSplitResult	Data split result. This contains references to the training and evaluation data tables that were used to train the model.
EvaluationMetrics	Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models.
GlobalExplanation	Global explanations containing the top most important features after training.
KmeansEnums
MultiClassClassificationMetrics	Evaluation metrics for multi-class classification/classifier models.
RankingMetrics	Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.
RegressionMetrics	Evaluation metrics for regression and explicit feedback type matrix factorization models.
SeasonalPeriod
TrainingRun	Information about a single training query run for the model.

Enums

DataFrequency	Type of supported data frequency for time series forecasting models.
DataSplitMethod	Indicates the method to split input data into multiple tables.
DistanceType	Distance metric used to compute the distance between two points.
FeedbackType	Indicates the training algorithm to use for matrix factorization models.
HolidayRegion	Type of supported holiday regions for time series forecasting models.
LearnRateStrategy	Indicates the learning rate optimization strategy to use.
LossType	Loss metric to evaluate model training performance.
ModelType	Indicates the type of the Model.
OptimizationStrategy	Indicates the optimization strategy used for training.