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v1

latestOpenAPI 3.0.0Creative Commons Attribution 3.02026-07-1342224376.9 KB
models

Patch specific fields in the specified model. # IAM Permissions Requires the bigquery.models.updateMetadata permission on the model.

patch/projects/{+projectId}/datasets/{+datasetId}/models/{+modelId}

Path parameters

projectIdstring required

Required. Project ID of the model to patch.

datasetIdstring required

Required. Dataset ID of the model to patch.

modelIdstring required

Required. Model ID of the model to patch.

Request body

defaultTrialIdstring int64

Output only. The default trial_id to use in TVFs when the trial_id is not passed in. For single-objective hyperparameter tuning models, this is the best trial ID. For multi-objective hyperparameter tuning models, this is the smallest trial ID among all Pareto optimal trials.

etagstring

Output only. A hash of this resource.

descriptionstring

Optional. A user-friendly description of this model.

friendlyNamestring

Optional. A descriptive name for this model.

locationstring

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

labelsobject

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.

creationTimestring int64

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

expirationTimestring int64

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.

lastModifiedTimestring int64

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

modelType'MODEL_TYPE_UNSPECIFIED' | 'LINEAR_REGRESSION' | 'LOGISTIC_REGRESSION' | 'KMEANS' | 'MATRIX_FACTORIZATION' | 'DNN_CLASSIFIER' | 'TENSORFLOW' | 'DNN_REGRESSOR' | 'XGBOOST' | 'BOOSTED_TREE_REGRESSOR' | 'BOOSTED_TREE_CLASSIFIER' | 'ARIMA' | 'AUTOML_REGRESSOR' | 'AUTOML_CLASSIFIER' | 'PCA' | 'DNN_LINEAR_COMBINED_CLASSIFIER' | 'DNN_LINEAR_COMBINED_REGRESSOR' | 'AUTOENCODER' | 'ARIMA_PLUS' | 'ARIMA_PLUS_XREG' | 'RANDOM_FOREST_REGRESSOR' | 'RANDOM_FOREST_CLASSIFIER' | 'TENSORFLOW_LITE' | 'ONNX' | 'TRANSFORM_ONLY' | 'CONTRIBUTION_ANALYSIS'

Output only. Type of the model resource.

optimalTrialIdsstring[]

Output only. For single-objective hyperparameter tuning models, it only contains the best trial. For multi-objective hyperparameter tuning models, it contains all Pareto optimal trials sorted by trial_id.

bestTrialIdstring int64

The best trial_id across all training runs.

Response

Successful response