hsml.sklearn.signature #

create_model #

create_model(
    name: str,
    version: int | None = None,
    metrics: dict | None = None,
    description: str | None = None,
    input_example: pandas.DataFrame
    | pandas.Series
    | numpy.ndarray
    | list
    | None = None,
    model_schema: ModelSchema | None = None,
    feature_view: FeatureView | None = None,
    training_dataset_version: int | None = None,
) -> Model

Create an SkLearn model metadata object.

Lazy

This method is lazy and does not persist any metadata or uploads model artifacts in the model registry on its own. To save the model object and the model artifacts, call the save() method with a local file path to the directory containing the model artifacts.

PARAMETER	DESCRIPTION
`name`	Name of the model to create. TYPE: `str`
`version`	Optionally version of the model to create, defaults to `None` and will create the model with incremented version from the last version in the model registry. TYPE: `int \| None` DEFAULT: `None`
`metrics`	Optionally a dictionary with model evaluation metrics (e.g., accuracy, MAE) TYPE: `dict \| None` DEFAULT: `None`
`description`	Optionally a string describing the model, defaults to empty string `""`. TYPE: `str \| None` DEFAULT: `None`
`input_example`	Optionally an input example that represents a single input for the model, defaults to `None`. TYPE: `pandas.DataFrame \| pandas.Series \| numpy.ndarray \| list \| None` DEFAULT: `None`
`model_schema`	Optionally a model schema for the model inputs and/or outputs. TYPE: `ModelSchema \| None` DEFAULT: `None`
`feature_view`	Optionally a feature view object returned by querying the feature store. If the feature view is not provided, the model will not have access to provenance. TYPE: `FeatureView \| None` DEFAULT: `None`
`training_dataset_version`	Optionally a training dataset version. If training dataset version is not provided, but the feature view is provided, the training dataset version used will be the last accessed training dataset of the feature view, within the code/notebook that reads the feature view and training dataset and then creates the model. TYPE: `int \| None` DEFAULT: `None`

RETURNS	DESCRIPTION
`Model`	The model metadata object.