Class LabelEncoder (2.30.0)

LabelEncoder(
    min_frequency: typing.Optional[int] = None,
    max_categories: typing.Optional[int] = None,
)

Encode target labels with value between 0 and n_classes-1.

This transformer should be used to encode target values, i.e. y, and not the input X.

Methods

LabelEncoder(
    min_frequency: typing.Optional[int] = None,
    max_categories: typing.Optional[int] = None,
)

Encode target labels with value between 0 and n_classes-1.

This transformer should be used to encode target values, i.e. y, and not the input X.

__init__(min_frequency=None, max_categories=None)

API documentation for __init__ method.

fit(y)

Fit label encoder.

Returns
Type	Description
`LabelEncoder`	Fitted encoder.

fit_transform(y)

API documentation for fit_transform method.

get_params(deep=True)

Get parameters for this estimator.

Parameter
Name	Description
`deep`	`bool, default True` Default `True`. If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns
Type	Description
`Dictionary`	A dictionary of parameter names mapped to their values.

to_gbq(model_name, replace=False)

Save the transformer as a BigQuery model.

Parameters
Name	Description
`model_name`	`str` The name of the model.
`replace`	`bool, default False` Determine whether to replace if the model already exists. Default to False.

transform(y)

Transform y using label encoding.

Returns
Type	Description
`bigframes.dataframe.DataFrame`	The result is an array-like of values.