evalml.preprocessing.KMeansSMOTETVSplit

class evalml.preprocessing.KMeansSMOTETVSplit(sampling_strategy='auto', k_neighbors=2, test_size=None, random_seed=0, **kwargs)

Splits the data into training and validation sets and balances the training data using K-Means SMOTE. Keeps the validation data the same. Works only on continuous, numeric data.

Methods

__init__	Create a TV or CV data splitter instance
get_n_splits	Returns the number of splits of this object.
split	Splits and returns the sampled training data using the data sampler provided.
transform_sample	Transforms the input data with the balancing strategy.

Class Inheritance

evalml.preprocessing.KMeansSMOTECVSplit.transform_sample evalml.preprocessing.KMeansSMOTETVSplit.__init__