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Classes
AutoMLForecastingProto
AutoMLImageClassificationProto
AutoMLImageObjectDetectionProto
AutoMLImageSegmentationProto
AutoMLTablesProto
AutoMLTextClassificationProto
AutoMLTextExtractionProto
AutoMLTextSentimentProto
AutoMLVideoActionRecognitionProto
AutoMLVideoClassificationProto
AutoMLVideoObjectTrackingProto
AutoMlForecasting
A TrainingJob that trains and uploads an AutoML Forecasting Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecasting
AutoMlForecasting.Builder
A TrainingJob that trains and uploads an AutoML Forecasting Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecasting
AutoMlForecastingInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs
AutoMlForecastingInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs
AutoMlForecastingInputs.Granularity
A duration of time expressed in time granularity units.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity
AutoMlForecastingInputs.Granularity.Builder
A duration of time expressed in time granularity units.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity
AutoMlForecastingInputs.Transformation
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation
AutoMlForecastingInputs.Transformation.AutoTransformation
Training pipeline will infer the proper transformation based on the statistic of dataset.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.AutoTransformation
AutoMlForecastingInputs.Transformation.AutoTransformation.Builder
Training pipeline will infer the proper transformation based on the statistic of dataset.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.AutoTransformation
AutoMlForecastingInputs.Transformation.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation
AutoMlForecastingInputs.Transformation.CategoricalTransformation
Training pipeline will perform following transformation functions.
The categorical string as is--no change to case, punctuation, spelling, tense, and so on.
Convert the category name to a dictionary lookup index and generate an embedding for each index.
Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.CategoricalTransformation
AutoMlForecastingInputs.Transformation.CategoricalTransformation.Builder
Training pipeline will perform following transformation functions.
The categorical string as is--no change to case, punctuation, spelling, tense, and so on.
Convert the category name to a dictionary lookup index and generate an embedding for each index.
Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.CategoricalTransformation
AutoMlForecastingInputs.Transformation.NumericTransformation
Training pipeline will perform following transformation functions.
The value converted to float32.
The z_score of the value.
log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
A boolean value that indicates whether the value is valid.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.NumericTransformation
AutoMlForecastingInputs.Transformation.NumericTransformation.Builder
Training pipeline will perform following transformation functions.
The value converted to float32.
The z_score of the value.
log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
A boolean value that indicates whether the value is valid.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.NumericTransformation
AutoMlForecastingInputs.Transformation.TextTransformation
Training pipeline will perform following transformation functions.
The text as is--no change to case, punctuation, spelling, tense, and so on.
Convert the category name to a dictionary lookup index and generate an embedding for each index.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.TextTransformation
AutoMlForecastingInputs.Transformation.TextTransformation.Builder
Training pipeline will perform following transformation functions.
The text as is--no change to case, punctuation, spelling, tense, and so on.
Convert the category name to a dictionary lookup index and generate an embedding for each index.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.TextTransformation
AutoMlForecastingInputs.Transformation.TimestampTransformation
Training pipeline will perform following transformation functions.
Apply the transformation functions for Numerical columns.
Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column.
Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.TimestampTransformation
AutoMlForecastingInputs.Transformation.TimestampTransformation.Builder
Training pipeline will perform following transformation functions.
Apply the transformation functions for Numerical columns.
Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column.
Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation.TimestampTransformation
AutoMlForecastingMetadata
Model metadata specific to AutoML Forecasting.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingMetadata
AutoMlForecastingMetadata.Builder
Model metadata specific to AutoML Forecasting.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingMetadata
AutoMlImageClassification
A TrainingJob that trains and uploads an AutoML Image Classification Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassification
AutoMlImageClassification.Builder
A TrainingJob that trains and uploads an AutoML Image Classification Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassification
AutoMlImageClassificationInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs
AutoMlImageClassificationInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs
AutoMlImageClassificationMetadata
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationMetadata
AutoMlImageClassificationMetadata.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationMetadata
AutoMlImageObjectDetection
A TrainingJob that trains and uploads an AutoML Image Object Detection Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetection
AutoMlImageObjectDetection.Builder
A TrainingJob that trains and uploads an AutoML Image Object Detection Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetection
AutoMlImageObjectDetectionInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs
AutoMlImageObjectDetectionInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs
AutoMlImageObjectDetectionMetadata
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionMetadata
AutoMlImageObjectDetectionMetadata.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionMetadata
AutoMlImageSegmentation
A TrainingJob that trains and uploads an AutoML Image Segmentation Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentation
AutoMlImageSegmentation.Builder
A TrainingJob that trains and uploads an AutoML Image Segmentation Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentation
AutoMlImageSegmentationInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs
AutoMlImageSegmentationInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs
AutoMlImageSegmentationMetadata
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationMetadata
AutoMlImageSegmentationMetadata.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationMetadata
AutoMlTables
A TrainingJob that trains and uploads an AutoML Tables Model.
Protobuf type google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTables
AutoMlTables.Builder
A TrainingJob that trains and uploads an AutoML Tables Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTables
AutoMlTablesInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs
AutoMlTablesInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs
AutoMlTablesInputs.Transformation
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation
AutoMlTablesInputs.Transformation.AutoTransformation
Training pipeline will infer the proper transformation based on the statistic of dataset.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.AutoTransformation
AutoMlTablesInputs.Transformation.AutoTransformation.Builder
Training pipeline will infer the proper transformation based on the statistic of dataset.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.AutoTransformation
AutoMlTablesInputs.Transformation.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation
AutoMlTablesInputs.Transformation.CategoricalArrayTransformation
Treats the column as categorical array and performs following transformation functions.
- For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Empty arrays treated as an embedding of zeroes.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.CategoricalArrayTransformation
AutoMlTablesInputs.Transformation.CategoricalArrayTransformation.Builder
Treats the column as categorical array and performs following transformation functions.
- For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Empty arrays treated as an embedding of zeroes.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.CategoricalArrayTransformation
AutoMlTablesInputs.Transformation.CategoricalTransformation
Training pipeline will perform following transformation functions.
- The categorical string as is--no change to case, punctuation, spelling, tense, and so on.
- Convert the category name to a dictionary lookup index and generate an embedding for each index.
- Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.CategoricalTransformation
AutoMlTablesInputs.Transformation.CategoricalTransformation.Builder
Training pipeline will perform following transformation functions.
- The categorical string as is--no change to case, punctuation, spelling, tense, and so on.
- Convert the category name to a dictionary lookup index and generate an embedding for each index.
- Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.CategoricalTransformation
AutoMlTablesInputs.Transformation.NumericArrayTransformation
Treats the column as numerical array and performs following transformation functions.
- All transformations for Numerical types applied to the average of the all elements.
- The average of empty arrays is treated as zero.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.NumericArrayTransformation
AutoMlTablesInputs.Transformation.NumericArrayTransformation.Builder
Treats the column as numerical array and performs following transformation functions.
- All transformations for Numerical types applied to the average of the all elements.
- The average of empty arrays is treated as zero.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.NumericArrayTransformation
AutoMlTablesInputs.Transformation.NumericTransformation
Training pipeline will perform following transformation functions.
- The value converted to float32.
- The z_score of the value.
- log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- A boolean value that indicates whether the value is valid.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.NumericTransformation
AutoMlTablesInputs.Transformation.NumericTransformation.Builder
Training pipeline will perform following transformation functions.
- The value converted to float32.
- The z_score of the value.
- log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- A boolean value that indicates whether the value is valid.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.NumericTransformation
AutoMlTablesInputs.Transformation.TextArrayTransformation
Treats the column as text array and performs following transformation functions.
- Concatenate all text values in the array into a single text value using a space (" ") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns.
- Empty arrays treated as an empty text.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.TextArrayTransformation
AutoMlTablesInputs.Transformation.TextArrayTransformation.Builder
Treats the column as text array and performs following transformation functions.
- Concatenate all text values in the array into a single text value using a space (" ") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns.
- Empty arrays treated as an empty text.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.TextArrayTransformation
AutoMlTablesInputs.Transformation.TextTransformation
Training pipeline will perform following transformation functions.
- The text as is--no change to case, punctuation, spelling, tense, and so on.
- Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Tokenization is based on unicode script boundaries.
- Missing values get their own lookup index and resulting embedding.
- Stop-words receive no special treatment and are not removed.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.TextTransformation
AutoMlTablesInputs.Transformation.TextTransformation.Builder
Training pipeline will perform following transformation functions.
- The text as is--no change to case, punctuation, spelling, tense, and so on.
- Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Tokenization is based on unicode script boundaries.
- Missing values get their own lookup index and resulting embedding.
- Stop-words receive no special treatment and are not removed.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.TextTransformation
AutoMlTablesInputs.Transformation.TimestampTransformation
Training pipeline will perform following transformation functions.
- Apply the transformation functions for Numerical columns.
- Determine the year, month, day,and weekday. Treat each value from the
- timestamp as a Categorical column.
- Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.TimestampTransformation
AutoMlTablesInputs.Transformation.TimestampTransformation.Builder
Training pipeline will perform following transformation functions.
- Apply the transformation functions for Numerical columns.
- Determine the year, month, day,and weekday. Treat each value from the
- timestamp as a Categorical column.
- Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesInputs.Transformation.TimestampTransformation
AutoMlTablesMetadata
Model metadata specific to AutoML Tables.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesMetadata
AutoMlTablesMetadata.Builder
Model metadata specific to AutoML Tables.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTablesMetadata
AutoMlTextClassification
A TrainingJob that trains and uploads an AutoML Text Classification Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextClassification
AutoMlTextClassification.Builder
A TrainingJob that trains and uploads an AutoML Text Classification Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextClassification
AutoMlTextClassificationInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextClassificationInputs
AutoMlTextClassificationInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextClassificationInputs
AutoMlTextExtraction
A TrainingJob that trains and uploads an AutoML Text Extraction Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextExtraction
AutoMlTextExtraction.Builder
A TrainingJob that trains and uploads an AutoML Text Extraction Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextExtraction
AutoMlTextExtractionInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextExtractionInputs
AutoMlTextExtractionInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextExtractionInputs
AutoMlTextSentiment
A TrainingJob that trains and uploads an AutoML Text Sentiment Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextSentiment
AutoMlTextSentiment.Builder
A TrainingJob that trains and uploads an AutoML Text Sentiment Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextSentiment
AutoMlTextSentimentInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextSentimentInputs
AutoMlTextSentimentInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlTextSentimentInputs
AutoMlVideoActionRecognition
A TrainingJob that trains and uploads an AutoML Video Action Recognition Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoActionRecognition
AutoMlVideoActionRecognition.Builder
A TrainingJob that trains and uploads an AutoML Video Action Recognition Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoActionRecognition
AutoMlVideoActionRecognitionInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoActionRecognitionInputs
AutoMlVideoActionRecognitionInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoActionRecognitionInputs
AutoMlVideoClassification
A TrainingJob that trains and uploads an AutoML Video Classification Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoClassification
AutoMlVideoClassification.Builder
A TrainingJob that trains and uploads an AutoML Video Classification Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoClassification
AutoMlVideoClassificationInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoClassificationInputs
AutoMlVideoClassificationInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoClassificationInputs
AutoMlVideoObjectTracking
A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoObjectTracking
AutoMlVideoObjectTracking.Builder
A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoObjectTracking
AutoMlVideoObjectTrackingInputs
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoObjectTrackingInputs
AutoMlVideoObjectTrackingInputs.Builder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoObjectTrackingInputs
ExportEvaluatedDataItemsConfig
Configuration for exporting test set predictions to a BigQuery table.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig
ExportEvaluatedDataItemsConfig.Builder
Configuration for exporting test set predictions to a BigQuery table.
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig
ExportEvaluatedDataItemsConfigProto
Interfaces
AutoMlForecastingInputs.GranularityOrBuilder
AutoMlForecastingInputs.Transformation.AutoTransformationOrBuilder
AutoMlForecastingInputs.Transformation.CategoricalTransformationOrBuilder
AutoMlForecastingInputs.Transformation.NumericTransformationOrBuilder
AutoMlForecastingInputs.Transformation.TextTransformationOrBuilder
AutoMlForecastingInputs.Transformation.TimestampTransformationOrBuilder
AutoMlForecastingInputs.TransformationOrBuilder
AutoMlForecastingInputsOrBuilder
AutoMlForecastingMetadataOrBuilder
AutoMlForecastingOrBuilder
AutoMlImageClassificationInputsOrBuilder
AutoMlImageClassificationMetadataOrBuilder
AutoMlImageClassificationOrBuilder
AutoMlImageObjectDetectionInputsOrBuilder
AutoMlImageObjectDetectionMetadataOrBuilder
AutoMlImageObjectDetectionOrBuilder
AutoMlImageSegmentationInputsOrBuilder
AutoMlImageSegmentationMetadataOrBuilder
AutoMlImageSegmentationOrBuilder
AutoMlTablesInputs.Transformation.AutoTransformationOrBuilder
AutoMlTablesInputs.Transformation.CategoricalArrayTransformationOrBuilder
AutoMlTablesInputs.Transformation.CategoricalTransformationOrBuilder
AutoMlTablesInputs.Transformation.NumericArrayTransformationOrBuilder
AutoMlTablesInputs.Transformation.NumericTransformationOrBuilder
AutoMlTablesInputs.Transformation.TextArrayTransformationOrBuilder
AutoMlTablesInputs.Transformation.TextTransformationOrBuilder
AutoMlTablesInputs.Transformation.TimestampTransformationOrBuilder
AutoMlTablesInputs.TransformationOrBuilder
AutoMlTablesInputsOrBuilder
AutoMlTablesMetadataOrBuilder
AutoMlTablesOrBuilder
AutoMlTextClassificationInputsOrBuilder
AutoMlTextClassificationOrBuilder
AutoMlTextExtractionInputsOrBuilder
AutoMlTextExtractionOrBuilder
AutoMlTextSentimentInputsOrBuilder
AutoMlTextSentimentOrBuilder
AutoMlVideoActionRecognitionInputsOrBuilder
AutoMlVideoActionRecognitionOrBuilder
AutoMlVideoClassificationInputsOrBuilder
AutoMlVideoClassificationOrBuilder
AutoMlVideoObjectTrackingInputsOrBuilder
AutoMlVideoObjectTrackingOrBuilder
ExportEvaluatedDataItemsConfigOrBuilder
Enums
AutoMlForecastingInputs.Transformation.TransformationDetailCase
AutoMlImageClassificationInputs.ModelType
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType
AutoMlImageClassificationMetadata.SuccessfulStopReason
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationMetadata.SuccessfulStopReason
AutoMlImageObjectDetectionInputs.ModelType
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType
AutoMlImageObjectDetectionMetadata.SuccessfulStopReason
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionMetadata.SuccessfulStopReason
AutoMlImageSegmentationInputs.ModelType
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType
AutoMlImageSegmentationMetadata.SuccessfulStopReason
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationMetadata.SuccessfulStopReason
AutoMlTablesInputs.AdditionalOptimizationObjectiveConfigCase
AutoMlTablesInputs.Transformation.TransformationDetailCase
AutoMlVideoActionRecognitionInputs.ModelType
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoActionRecognitionInputs.ModelType
AutoMlVideoClassificationInputs.ModelType
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoClassificationInputs.ModelType
AutoMlVideoObjectTrackingInputs.ModelType
Protobuf enum
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlVideoObjectTrackingInputs.ModelType