skclean.simulate_noise.BCNoise¶
-
class
skclean.simulate_noise.
BCNoise
(classifier, noise_level, random_state=None)¶ Boundary Consistent Noise- instances closer to boundary more likely to be noisy. In this implementation, “closeness” to decision boundary of a sample is measured using entropy of it’s class probabilities. A classifier with support for well calibrated class probabilities (i.e. predict_proba of scikit-learn API) is required.
Only supports binary classification for now. See [MVRN18] for details.
- Parameters
classifier (object) – A classifier instance supporting sklearn API.
noise_level (float) – percentage of labels to flip
random_state (int, default=None) – Set this value for reproducibility
Methods
__init__
(classifier, noise_level[, 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)