evalml.pipelines.components.SMOTENCSampler

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

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_default': 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

Inheritance diagram of SMOTENCSampler