skclean.handlers.CLNI¶
-
class
skclean.handlers.
CLNI
(classifier, detector, threshold=0.4, eps=0.99, n_jobs=1, random_state=None)¶ Iteratively detects and filters out mislabelled samples unless a stopping criterion is met. See [KZWG11] for details/usage.
- Parameters
classifier (object) – A classifier instance supporting sklearn API.
detector (BaseDetector) – To compute conf_score. All iterative handlers require this.
threshold (float, default=.4) – Samples with lower conf_score will be filtered out.
eps (float, default=.99) – Stopping criterion for main detection->cleaning loop, indicates ratio of total number of mislabelled samples identified in two successive iterations.
n_jobs (int, default=1) – No of parallel cpu cores to use
random_state (int, default=None) – Set this value for reproducibility
Methods
__init__
(classifier, detector[, threshold, …])Initialize self.
clean
(X, y)fit
(X, y[, conf_score])get_params
([deep])Get parameters for this estimator.
predict
(X)predict_proba
(X)score
(X, y[, sample_weight])Return the mean accuracy on the given test data and labels.
set_params
(**params)Set the parameters of this estimator.
Attributes
iterative