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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::ModelMonitoringObjectiveConfig::TrainingDataset.
Training Dataset information.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#bigquery_source
def bigquery_source() -> ::Google::Cloud::AIPlatform::V1::BigQuerySource
Returns
- (::Google::Cloud::AIPlatform::V1::BigQuerySource) — The BigQuery table of the unmanaged Dataset used to train this Model.
#bigquery_source=
def bigquery_source=(value) -> ::Google::Cloud::AIPlatform::V1::BigQuerySource
Parameter
- value (::Google::Cloud::AIPlatform::V1::BigQuerySource) — The BigQuery table of the unmanaged Dataset used to train this Model.
Returns
- (::Google::Cloud::AIPlatform::V1::BigQuerySource) — The BigQuery table of the unmanaged Dataset used to train this Model.
#data_format
def data_format() -> ::String
Returns
-
(::String) — Data format of the dataset, only applicable if the input is from
Google Cloud Storage.
The possible formats are:
"tf-record" The source file is a TFRecord file.
"csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.
#data_format=
def data_format=(value) -> ::String
Parameter
-
value (::String) — Data format of the dataset, only applicable if the input is from
Google Cloud Storage.
The possible formats are:
"tf-record" The source file is a TFRecord file.
"csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.
Returns
-
(::String) — Data format of the dataset, only applicable if the input is from
Google Cloud Storage.
The possible formats are:
"tf-record" The source file is a TFRecord file.
"csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.
#dataset
def dataset() -> ::String
Returns
- (::String) — The resource name of the Dataset used to train this Model.
#dataset=
def dataset=(value) -> ::String
Parameter
- value (::String) — The resource name of the Dataset used to train this Model.
Returns
- (::String) — The resource name of the Dataset used to train this Model.
#gcs_source
def gcs_source() -> ::Google::Cloud::AIPlatform::V1::GcsSource
Returns
- (::Google::Cloud::AIPlatform::V1::GcsSource) — The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
#gcs_source=
def gcs_source=(value) -> ::Google::Cloud::AIPlatform::V1::GcsSource
Parameter
- value (::Google::Cloud::AIPlatform::V1::GcsSource) — The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
Returns
- (::Google::Cloud::AIPlatform::V1::GcsSource) — The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
#logging_sampling_strategy
def logging_sampling_strategy() -> ::Google::Cloud::AIPlatform::V1::SamplingStrategy
Returns
- (::Google::Cloud::AIPlatform::V1::SamplingStrategy) — Strategy to sample data from Training Dataset. If not set, we process the whole dataset.
#logging_sampling_strategy=
def logging_sampling_strategy=(value) -> ::Google::Cloud::AIPlatform::V1::SamplingStrategy
Parameter
- value (::Google::Cloud::AIPlatform::V1::SamplingStrategy) — Strategy to sample data from Training Dataset. If not set, we process the whole dataset.
Returns
- (::Google::Cloud::AIPlatform::V1::SamplingStrategy) — Strategy to sample data from Training Dataset. If not set, we process the whole dataset.
#target_field
def target_field() -> ::String
Returns
- (::String) — The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.
#target_field=
def target_field=(value) -> ::String
Parameter
- value (::String) — The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.
Returns
- (::String) — The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.