evalml.pipelines.components.SMOTENCSampler

class evalml.pipelines.components.SMOTENCSampler(sampling_ratio=0.25, k_neighbors=5, n_jobs=- 1, random_seed=0, **kwargs)

SMOTENC Oversampler component. Uses SMOTENC to generate synthetic samples. Works on a mix of nomerical and categorical columns. Input data must be Woodwork type, and this component is only run during training and not during predict.

name = 'SMOTENC Oversampler'

model_family = 'none'

hyperparameter_ranges = {}

default_parameters = {'k_neighbors': 5, 'n_jobs': -1, 'sampling_ratio': 0.25, 'sampling_ratio_dict': None}

Instance attributes

needs_fitting
parameters	Returns the parameters which were used to initialize the component

Methods:

__init__	Initializes the oversampler component.
clone	Constructs a new component with the same parameters and random state.
describe	Describe a component and its parameters
fit	Fits the Oversampler to the data.
fit_transform	Fit and transform the data using the data sampler.
load	Loads component at file path
save	Saves component at file path
transform	No transformation needs to be done here.

Class Inheritance

evalml.pipelines.components.SMOTESampler.transform evalml.pipelines.components.SMOTENCSampler.__init__