DashAI.back.converters.StandardScaler

class StandardScaler(**kwargs)[source]

Scikit-learn’s Standard Scaler wrapper for DashAI.

Methods

`__init__`(**kwargs)
`changes_row_count`()	Indicates if the converter changes the number of rows in the dataset.
`fit`(x[, y])	Generic fit method for sklearn transformers
`fit_transform`(X[, y])	Fit to data, then transform it.
`get_feature_names_out`([input_features])	Get output feature names for transformation.
`get_metadata_routing`()	Get metadata routing of this object.
`get_params`([deep])	Get parameters for this estimator.
`get_schema`()	Generates the component related Json Schema.
`inverse_transform`(X[, copy])	Scale back the data to the original representation.
`partial_fit`(X[, y, sample_weight])	Online computation of mean and std on X for later scaling.
`set_fit_request`(*[, x])	Request metadata passed to the `fit` method.
`set_inverse_transform_request`(*[, copy])	Request metadata passed to the `inverse_transform` method.
`set_output`(*[, transform])	Set output container.
`set_params`(**params)	Set the parameters of this estimator.
`set_partial_fit_request`(*[, sample_weight])	Request metadata passed to the `partial_fit` method.
`set_transform_request`(*[, x])	Request metadata passed to the `transform` method.
`transform`(x[, y])	Generic transform method for sklearn transformers
`validate_and_transform`(raw_data)	It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.

Attributes

`DESCRIPTION`
`TYPE`