sampler_base¶
Module Contents¶
Classes Summary¶
Base class for all custom samplers. |
Contents¶
-
class
evalml.preprocessing.data_splitters.sampler_base.SamplerBase(random_seed=0)[source]¶ Base class for all custom samplers.
- Parameters
random_seed (int) – The seed to use for random sampling. Defaults to 0.
Methods
Resample the input data with this sampling strategy.
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abstract
fit_resample(self, X, y)[source]¶ Resample the input data with this sampling strategy.
- Parameters
X (pd.DataFrame) – Training data to fit and resample
y (pd.Series) – Training data targets to fit and resample
- Returns
resampled X and y data for oversampling or indices to keep for undersampling
- Return type
Tuple(pd.DataFrame, pd.Series) or list