saealib.SklearnClassificationSurrogate

class saealib.SklearnClassificationSurrogate(estimator)

ベースクラス: ComparisonSurrogate

Surrogate adapter for scikit-learn compatible binary classifiers.

Wraps any estimator that implements fit(X, y) and predict_proba(X). train_y must be binary labels {0, 1}.

パラメータ:

estimator (sklearn estimator) -- A scikit-learn compatible classifier with predict_proba support (e.g. SVC(probability=True) or RandomForestClassifier()).

例外:

ImportError -- If scikit-learn is not installed.

Methods

__init__
contract	Return the surrogate model contract.
fit	Fit the classifier.
post_fit	Post-fit lifecycle hook; override to inject custom processing.
predict	Delegate to predict_proba.
predict_proba	Return class-1 probability estimates.
with_post_fit	Return a copy of this surrogate with fn appended to the post-fit hook.

Method Details

SklearnClassificationSurrogate.__init__(estimator)

パラメータ:

estimator (object)

戻り値の型:

None

SklearnClassificationSurrogate.contract()

Return the surrogate model contract.

戻り値の型:

ComponentContract

SklearnClassificationSurrogate.fit(train_x, train_y)

Fit the classifier.

パラメータ:

• train_x (np.ndarray) -- Training input data. shape: (n_samples, n_features)

• train_y (np.ndarray) -- Binary labels. shape: (n_samples,), values in {0, 1}.

戻り値の型:

None

SklearnClassificationSurrogate.post_fit(train_x, train_y, ctx=None)

Post-fit lifecycle hook; override to inject custom processing.

パラメータ:

• train_x (np.ndarray) -- Training input data used for this fit. shape: (n_samples, n_features)

• train_y (np.ndarray) -- Training output data used for this fit. shape: (n_samples, n_obj)

• ctx (OptimizationState or None, optional) -- Current optimization context.

戻り値の型:

None

SklearnClassificationSurrogate.predict(test_x)

Delegate to predict_proba.

パラメータ:

test_x (ndarray)

戻り値の型:

SurrogatePrediction

SklearnClassificationSurrogate.predict_proba(test_x)

Return class-1 probability estimates.

パラメータ:

test_x (np.ndarray) -- Input data. shape: (n_samples, n_features) or (n_features,)

戻り値:

value shape: (n_samples, 1), values in [0, 1].

戻り値の型:

SurrogatePrediction

SklearnClassificationSurrogate.with_post_fit(fn)

Return a copy of this surrogate with fn appended to the post-fit hook.

パラメータ:

fn (callable) -- fn(train_x, train_y, ctx) -> None

戻り値:

Shallow copy with the hook registered.

戻り値の型:

Surrogate