skclean.simulate_noise.CCNoise

class skclean.simulate_noise.CCNoise(lcm=None, random_state=None)

Class Conditional Noise: general version of flip_labels_uniform- a sample’s probability of getting mislabelled and it’s new (noisy) label depends on it’s true label, but not features. Simple wrapper around flip_labels_cc mainly for use in Pipeline.

Parameters

  • lcm (np.ndarray) – Short for Label Confusion Matrix. lcm[i,j] denotes the probability of a sample with true label i getting mislabelled as j.

  • random_state (int, default=None) – Set this value for reproducibility

Methods

__init__([lcm, random_state])

Initialize self.

fit_transform(X[, y])

Fit to data, then transform it.

get_params([deep])

Get parameters for this estimator.

set_params(**params)

Set the parameters of this estimator.

simulate_noise(X, y)

transform(X)