Struct google_bigquery2::api::Model[][src]

pub struct Model {
Show 15 fields pub best_trial_id: Option<String>, pub creation_time: Option<String>, pub description: Option<String>, pub encryption_configuration: Option<EncryptionConfiguration>, pub etag: Option<String>, pub expiration_time: Option<String>, pub feature_columns: Option<Vec<StandardSqlField>>, pub friendly_name: Option<String>, pub label_columns: Option<Vec<StandardSqlField>>, pub labels: Option<HashMap<String, String>>, pub last_modified_time: Option<String>, pub location: Option<String>, pub model_reference: Option<ModelReference>, pub model_type: Option<String>, pub training_runs: Option<Vec<TrainingRun>>,
}
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Activities

This type is used in activities, which are methods you may call on this type or where this type is involved in. The list links the activity name, along with information about where it is used (one of request and response).

Fields

best_trial_id: Option<String>

The best trial_id across all training runs.

creation_time: Option<String>

Output only. The time when this model was created, in millisecs since the epoch.

description: Option<String>

Optional. A user-friendly description of this model.

encryption_configuration: Option<EncryptionConfiguration>

Custom encryption configuration (e.g., Cloud KMS keys). This shows the encryption configuration of the model data while stored in BigQuery storage. This field can be used with PatchModel to update encryption key for an already encrypted model.

etag: Option<String>

Output only. A hash of this resource.

expiration_time: Option<String>

Optional. The time when this model expires, in milliseconds since the epoch. If not present, the model will persist indefinitely. Expired models will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created models.

feature_columns: Option<Vec<StandardSqlField>>

Output only. Input feature columns that were used to train this model.

friendly_name: Option<String>

Optional. A descriptive name for this model.

label_columns: Option<Vec<StandardSqlField>>

Output only. Label columns that were used to train this model. The output of the model will have a “predicted_” prefix to these columns.

labels: Option<HashMap<String, String>>

The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.

last_modified_time: Option<String>

Output only. The time when this model was last modified, in millisecs since the epoch.

location: Option<String>

Output only. The geographic location where the model resides. This value is inherited from the dataset.

model_reference: Option<ModelReference>

Required. Unique identifier for this model.

model_type: Option<String>

Output only. Type of the model resource.

training_runs: Option<Vec<TrainingRun>>

Output only. Information for all training runs in increasing order of start_time.

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