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
.
Parameters |
|
---|---|
Name | Description |
min_frequency |
Optional[int], default None
Specifies the minimum frequency below which a category will be considered infrequent. Default None. int: categories with a smaller cardinality will be considered infrequent as ßindex 0. |
max_categories |
Optional[int], default None
Specifies an upper limit to the number of output features for each input feature when considering infrequent categories. If there are infrequent categories, max_categories includes the category representing the infrequent categories along with the frequent categories. Default None. Set limit to 1,000,000. |
Methods
__repr__
__repr__()
Print the estimator's constructor with all non-default parameter values.
fit
fit(
y: typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series]
) -> bigframes.ml.preprocessing.LabelEncoder
Fit label encoder.
Parameter | |
---|---|
Name | Description |
y |
bigframes.dataframe.DataFrame or bigframes.series.Series
The DataFrame or Series with training data. |
Returns | |
---|---|
Type | Description |
LabelEncoder |
Fitted encoder. |
fit_transform
fit_transform(
y: typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series]
) -> bigframes.dataframe.DataFrame
API documentation for fit_transform
method.
get_params
get_params(deep: bool = True) -> typing.Dict[str, typing.Any]
Get parameters for this estimator.
Parameter | |
---|---|
Name | Description |
deep |
bool, default True
Default |
Returns | |
---|---|
Type | Description |
Dictionary |
A dictionary of parameter names mapped to their values. |
to_gbq
to_gbq(model_name: str, replace: bool = False) -> bigframes.ml.base._T
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
transform(
y: typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series]
) -> bigframes.dataframe.DataFrame
Transform y using label encoding.
Parameter | |
---|---|
Name | Description |
y |
bigframes.dataframe.DataFrame or bigframes.series.Series
The DataFrame or Series to be transformed. |
Returns | |
---|---|
Type | Description |
bigframes.dataframe.DataFrame |
The result is an array-like of values. |