DeepchecksModelClient.version#
- DeepchecksModelClient.version(name: str, schema: Union[str, Path, TextIOBase, DataSchema] = None, feature_importance: Optional[Union[Dict[str, float], pd.Series[float]]] = None, model_classes: Optional[Sequence[str]] = None, create_if_not_exists: bool = True) Optional[DeepchecksModelVersionClient]#
Create a new model version.
- Parameters
- namestr
Name to display for new version
- schemaUnion[str, pathlib.Path, io.TextIOBase, Dict[str, Dict[str, Any]]], default: None
path to a schema file, file like object with schema, or a dictionary representing a schema. Can be none if getting existing model version. This method expects that provided file will be in the next yaml format:
- features:
foo: <feature-type> bar: <feature-type>
- additional_data:
foo: <feature-type> bar: <feature-type>
- where ‘feature-type’ is one of:
‘numeric’
‘integer’
‘categorical’
‘boolean’
‘text’
‘array_float’
‘array_float_2d’
‘datetime’
- feature_importanceUnion[Dict[str, float], pandas.Series[float]], default: None
A dictionary or pandas series of feature names and their feature importance value.
- model_classesOptional[Sequence[str]], default: None
List of classes used by the model. Must define classes in order to send probabilities.
- create_if_not_existsbool, default: True
If True, create the model version if it does not exist (requires passing schema), else return None if not exists.
- Returns
- DeepchecksModelVersionClient
Client to interact with the newly created version.