Adds a surrogate model to an existing a model without uploading an artifact.
Note:
Note: Before calling this function, you must have already added a model using
add_model.
| Input Parameter | Type | Default | Description |
|---|---|---|---|
| project_id | str | None | The unique identifier for the project. |
| model_id | str | None | A unique identifier for the model. Must be a lowercase string between 2-30 characters containing only alphanumeric characters and underscores. Additionally, it must not start with a numeric character. |
| deployment | Optional [fdl.core_objects.DeploymentOptions] | None | A DeploymentOptions object containing information about the model deployment. |
| cache_global_impact_importance | Optional [bool] | True | If True, global feature impact and global feature importance will be precomputed and cached when the model is registered. |
| cache_global_pdps | Optional [bool] | False | If True, global partial dependence plots will be precomputed and cached when the model is registered. |
| cache_dataset | Optional [bool] | True | If True, histogram information for the baseline dataset will be precomputed and cached when the model is registered. |
PROJECT_ID = 'example_project'
MODEL_ID = 'example_model'
client.add_model_surrogate(
project_id=PROJECT_ID,
model_id=MODEL_ID
)
| Return Type | Description |
|---|---|
| str | A message confirming that a surrogate model was generated. |