Namespace Google.Apis.Bigquery.v2.Data

Classes

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.

Argument

Input/output argument of a function or a stored procedure.

ArimaCoefficients

Arima coefficients.

ArimaFittingMetrics

ARIMA model fitting metrics.

ArimaModelInfo

Arima model information.

ArimaOrder

Arima order, can be used for both non-seasonal and seasonal parts.

ArimaResult

(Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results.

BigQueryModelTraining

BigtableColumn

BigtableColumnFamily

BigtableOptions

BinaryClassificationMetrics

Evaluation metrics for binary classification/classifier models.

BinaryConfusionMatrix

Confusion matrix for binary classification models.

BqmlIterationResult

BqmlTrainingRun

BqmlTrainingRun.TrainingOptionsData

[Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.

CategoricalValue

Representative value of a categorical feature.

CategoryCount

Represents the count of a single category within the cluster.

Cluster

Message containing the information about one cluster.

ClusterInfo

Information about a single cluster for clustering model.

Clustering

ClusteringMetrics

Evaluation metrics for clustering models.

ConfusionMatrix

Confusion matrix for multi-class classification models.

CsvOptions

Dataset

Dataset.AccessData

DatasetList

DatasetList.DatasetsData

DatasetReference

DataSplitResult

Data split result. This contains references to the training and evaluation data tables that were used to train the model.

DestinationTableProperties

EncryptionConfiguration

Entry

A single entry in the confusion matrix.

ErrorProto

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.

ExplainQueryStage

ExplainQueryStep

ExternalDataConfiguration

FeatureValue

Representative value of a single feature within the cluster.

GetQueryResultsResponse

GetServiceAccountResponse

GoogleSheetsOptions

HivePartitioningOptions

IterationResult

Information about a single iteration of the training run.

Job

JobCancelResponse

JobConfiguration

JobConfigurationExtract

JobConfigurationLoad

JobConfigurationQuery

JobConfigurationTableCopy

JobList

JobList.JobsData

JobReference

JobStatistics

JobStatistics.ReservationUsageData

JobStatistics2

JobStatistics2.ReservationUsageData

JobStatistics3

JobStatistics4

JobStatus

ListModelsResponse

ListRoutinesResponse

LocationMetadata

BigQuery-specific metadata about a location. This will be set on google.cloud.location.Location.metadata in Cloud Location API responses.

MaterializedViewDefinition

Model

ModelDefinition

ModelDefinition.ModelOptionsData

[Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.

ModelReference

MultiClassClassificationMetrics

Evaluation metrics for multi-class classification/classifier models.

ProjectList

ProjectList.ProjectsData

ProjectReference

QueryParameter

QueryParameterType

QueryParameterType.StructTypesData

QueryParameterValue

QueryRequest

QueryResponse

QueryTimelineSample

RangePartitioning

RangePartitioning.RangeData

[TrustedTester] [Required] Defines the ranges for range partitioning.

RegressionMetrics

Evaluation metrics for regression and explicit feedback type matrix factorization models.

Routine

A user-defined function or a stored procedure.

RoutineReference

Row

A single row in the confusion matrix.

ScriptStackFrame

ScriptStatistics

StandardSqlDataType

The type of a variable, e.g., a function argument. Examples: INT64: {type_kind="INT64"} ARRAY: {type_kind="ARRAY", array_element_type="STRING"} STRUCT>: {type_kind="STRUCT", struct_type={fields=[ {name="x", type={type_kind="STRING"}}, {name="y", type={type_kind="ARRAY", array_element_type="DATE"}} ]}}