saealib.SklearnClassificationSurrogate#

class saealib.SklearnClassificationSurrogate(estimator)[source]#

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}.

Parameters:: estimator (sklearn estimator) – A scikit-learn compatible classifier with predict_proba support (e.g. SVC(probability=True) or RandomForestClassifier()).
Raises:: 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)[source]#

SklearnClassificationSurrogate.contract()#

Return the surrogate model contract.

SklearnClassificationSurrogate.fit(train_x, train_y)[source]#

Fit the classifier.

Parameters:

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}.

Return type:

None

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

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

Parameters:

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.

Return type:

None

SklearnClassificationSurrogate.predict(test_x)#

Delegate to predict_proba.

SklearnClassificationSurrogate.predict_proba(test_x)[source]#

Return class-1 probability estimates.

Parameters:: test_x (np.ndarray) – Input data. shape: (n_samples, n_features) or (n_features,)
Returns:: value shape: (n_samples, 1), values in [0, 1].
Return type:: SurrogatePrediction

SklearnClassificationSurrogate.with_post_fit(fn)#

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