skclean.handlers.FilterCV¶
-
class
skclean.handlers.
FilterCV
(classifier, detector=None, thresholds=None, fracs_to_filter=None, cv=5, n_jobs=1, random_state=None)¶ For quickly finding best cutoff point for Filter i.e. threshold or fraction_to_filter. This avoids recomputing conf_score for each hyper-parameter value as opposed to say GridSearchCV. See [SMartinezMunozSuarez18] for details/usage.
- Parameters
classifier (object) – A classifier instance supporting sklearn API.
detector (BaseDetector or None, default=None) – To compute conf_score. Set it to None only if conf_score is expected in fit() (e.g. when used inside a Pipeline with a BaseDetector preceding it). Otherwise a Detector must be supplied during instantiation.
thresholds (list, default=None) – A list of thresholds to choose the best one from
fracs_to_filter (list, default=None) – A list of percentages to choose the best one from
cv (int, cross-validation generator or an iterable, default=None) – If None, uses 5-fold stratified k-fold if int, no of folds to use in stratified k-fold
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, thresholds, …])Initialize self.
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