saealib.ComparisonSurrogate#
- class saealib.ComparisonSurrogate[source]#
Bases:
SurrogateBase class for relative-fitness (comparison) surrogates.
Subclass this when
train_yholds binary comparison labels{0, 1}and predictions are win-probability estimates in[0, 1].predict_probais the primary interface;predictdelegates to it by default so that managers designed forSurrogatestill work.
Methods
Return the surrogate model contract. |
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Fit the surrogate model. |
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Post-fit lifecycle hook; override to inject custom processing. |
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Delegate to |
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Return win-probability estimates. |
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Return a copy of this surrogate with |
Method Details
- ComparisonSurrogate.__init__()#
- ComparisonSurrogate.contract()#
Return the surrogate model contract.
- Return type:
- abstractmethod ComparisonSurrogate.fit(train_x, train_y)#
Fit the surrogate model.
- Parameters:
train_x (np.ndarray) – Training input data. shape: (n_samples, n_features)
train_y (np.ndarray) – Training output data. shape: (n_samples, n_obj) For n_obj == 1, shape (n_samples,) is also accepted.
- Return type:
None
- ComparisonSurrogate.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
- ComparisonSurrogate.predict(test_x)[source]#
Delegate to
predict_proba.- Parameters:
test_x (ndarray)
- Return type: