snowflake.ml.modeling.preprocessing.OrdinalEncoderΒΆ
- class snowflake.ml.modeling.preprocessing.OrdinalEncoder(*, categories: Union[str, Dict[str, Union[ndarray[Any, dtype[int64]], ndarray[Any, dtype[float64]], ndarray[Any, dtype[str_]], ndarray[Any, dtype[bool_]]]]] = 'auto', handle_unknown: str = 'error', unknown_value: Optional[Union[int, float]] = None, encoded_missing_value: Union[int, float] = nan, input_cols: Optional[Union[str, Iterable[str]]] = None, output_cols: Optional[Union[str, Iterable[str]]] = None, drop_input_cols: Optional[bool] = False)ΒΆ
Bases:
BaseTransformer
Encodes categorical features as an integer array.
In other words, each category (i.e., distinct numeric or string value) is assigned an integer value, starting with zero.
For more details on what this transformer does, see sklearn.preprocessing.OrdinalEncoder.
- Args:
- categories: The string βautoβ (the default) causes the categories to be extracted from the input columns.
To specify the categories yourself, pass a dictionary mapping the column name to an ndarray containing the categories.
- handle_unknown: Specifies how unknown categories are handled during transformation. Applicable only if
categories is not βautoβ. Valid values are:
βerrorβ: Raise an error if an unknown category is present during transform (default).
- βuse_encoded_valueβ: When an unknown category is encountered during transform, the specified
encoded_missing_value (below) is used.
- unknown_value: When the parameter handle_unknown is set to βuse_encoded_valueβ, this parameter is required and
will set the encoded value of unknown categories. It has to be distinct from the values used to encode any of the categories in fit.
encoded_missing_value: The value to be used to encode unknown categories. input_cols: The name(s) of one or more columns in a DataFrame containing a feature to be encoded. output_cols: The name(s) of one or more columns in a DataFrame in which results will be stored. The number of
columns specified must match the number of input columns.
drop_input_cols: Remove input columns from output if set True. False by default.
- Attributes:
- categories_ (dict of ndarray): The categories of each feature determined during fitting. Maps input column
names to an array of the detected categories. Attributes are valid only after fit() has been called.
Methods
fit
(dataset)Fit the OrdinalEncoder to dataset.
transform
(dataset)Transform dataset to ordinal codes.