multiaug.augmenters.tabular package¶

Submodules¶

class multiaug.augmenters.tabular.gaussian_perturbation.GaussianPerturbation(method: str = 'variance', fraction: float = 0.1)¶

Apply featurewise Gaussian noise to each feature in a sample.

Parameters:	method (str) – Method to use to determine the noise (currently variance is the only supported method). If ‘variance’ then the noise is determined by taking a fraction of the variance (across the individual features) for each feature and adding it the the original feature. fraction (float) – Fraction of noise to add to sample.

apply(data: numpy.ndarray, row_ids: numpy.ndarray)¶

Apply the augmentation to the samples.

Parameters:	data (np.ndarray) – Entire dataset such that the noise can be determined relative to the entire dataset. row_ids (np.ndarray) – The indices of the samples to which to apply noise.
Returns:	Augmented data
Return type:	np.ndarray