Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ModelMonitoringObjectiveConfig::TrainingDataset (v0.10.0)

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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.