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"}} ]}}
StandardSqlField
A field or a column.
StandardSqlStructType
Streamingbuffer
Table
TableCell
TableDataInsertAllRequest
TableDataInsertAllRequest.RowsData
TableDataInsertAllResponse
TableDataInsertAllResponse.InsertErrorsData
TableDataList
TableFieldSchema
TableFieldSchema.CategoriesData
[Optional] The categories attached to this field, used for field-level access control.
TableFieldSchema.PolicyTagsData
TableList
TableList.TablesData
TableList.TablesData.ViewData
Additional details for a view.
TableReference
TableRow
TableSchema
TimePartitioning
TrainingOptions
TrainingRun
Information about a single training query run for the model.