- 1.25.0 (latest)
- 1.24.0
- 1.22.0
- 1.21.0
- 1.20.0
- 1.19.0
- 1.18.0
- 1.17.0
- 1.16.0
- 1.15.0
- 1.14.0
- 1.13.0
- 1.12.0
- 1.11.1
- 1.10.0
- 1.9.0
- 1.8.0
- 1.7.0
- 1.6.0
- 1.5.0
- 1.4.0
- 1.3.0
- 1.2.0
- 1.1.0
- 1.0.0
- 0.26.0
- 0.25.0
- 0.24.0
- 0.23.0
- 0.22.0
- 0.21.0
- 0.20.1
- 0.19.2
- 0.18.0
- 0.17.0
- 0.16.0
- 0.15.0
- 0.14.1
- 0.13.0
- 0.12.0
- 0.11.0
- 0.10.0
- 0.9.0
- 0.8.0
- 0.7.0
- 0.6.0
- 0.5.0
- 0.4.0
- 0.3.0
- 0.2.0
MaxAbsScaler()
Scale each feature by its maximum absolute value.
This estimator scales and translates each feature individually such that the maximal absolute value of each feature in the training set will be 1.0. It does not shift/center the data, and thus does not destroy any sparsity.
Methods
__repr__
__repr__()
Print the estimator's constructor with all non-default parameter values.
fit
fit(
X: typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series], y=None
) -> bigframes.ml.preprocessing.MaxAbsScaler
Compute the maximum absolute value to be used for later scaling.
Parameters | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.series.Series
The Dataframe or Series with training data. |
y |
default None
Ignored. |
Returns | |
---|---|
Type | Description |
MaxAbsScaler |
Fitted scaler. |
fit_transform
fit_transform(
X: typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series],
y: typing.Optional[
typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series]
] = None,
) -> bigframes.dataframe.DataFrame
Fit to data, then transform it.
Parameters | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.series.Series
Series or DataFrame of shape (n_samples, n_features). Input samples. |
y |
bigframes.dataframe.DataFrame or bigframes.series.Series
Series or DataFrame of shape (n_samples,) or (n_samples, n_outputs). Default None. Target values (None for unsupervised transformations). |
Returns | |
---|---|
Type | Description |
bigframes.dataframe.DataFrame |
DataFrame of shape (n_samples, n_features_new). Transformed DataFrame. |
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(
X: typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series]
) -> bigframes.dataframe.DataFrame
Scale the data.
Parameter | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.series.Series
The DataFrame or Series to be transformed. |
Returns | |
---|---|
Type | Description |
bigframes.dataframe.DataFrame |
Transformed result. |