From ea17da5d35044aef698a2b96e9aa136d8c719bb3 Mon Sep 17 00:00:00 2001 From: Villu Ruusmann Date: Wed, 20 Sep 2023 14:20:20 +0300 Subject: [PATCH] Renamed '_BaseEnsemble.recaller' attribute to 'controller' --- sklearn2pmml/ensemble/__init__.py | 27 +++++++++++++++------------ 1 file changed, 15 insertions(+), 12 deletions(-) diff --git a/sklearn2pmml/ensemble/__init__.py b/sklearn2pmml/ensemble/__init__.py index bfa2092..4f47845 100644 --- a/sklearn2pmml/ensemble/__init__.py +++ b/sklearn2pmml/ensemble/__init__.py @@ -181,7 +181,7 @@ def predict_proba(self, X, **predict_proba_params): class _BaseEnsemble(_BaseComposition): - def __init__(self, steps, recaller): + def __init__(self, steps, controller): for step in steps: if type(step) is not tuple: raise TypeError("Step is not a tuple") @@ -191,7 +191,10 @@ def __init__(self, steps, recaller): if not isinstance(predicate, (str, Predicate)): raise TypeError() self.steps = steps - self.recaller = recaller + if controller: + if not hasattr(controller, "transform"): + raise TypeError() + self.controller = controller @property def _steps(self): @@ -209,8 +212,8 @@ def set_params(self, **kwargs): return self def _to_evaluation_dataset(self, X): - if self.recaller is not None: - return self.recaller.transform(X) + if self.controller is not None: + return self.controller.transform(X) return X def _to_sparse(X, step_mask, step_result): @@ -262,8 +265,8 @@ def augment(self, X): class EstimatorChain(_BaseEnsemble): - def __init__(self, steps, recaller = None, multioutput = True): - super(EstimatorChain, self).__init__(steps, recaller) + def __init__(self, steps, controller = None, multioutput = True): + super(EstimatorChain, self).__init__(steps, controller) self.multioutput = multioutput def fit(self, X, y, **fit_params): @@ -324,8 +327,8 @@ def predict_proba(self, X): class SelectFirstEstimator(_BaseEnsemble): - def __init__(self, steps, recaller): - super(SelectFirstEstimator, self).__init__(steps, recaller) + def __init__(self, steps, controller): + super(SelectFirstEstimator, self).__init__(steps, controller) def fit(self, X, y, **fit_params): X_eval = self._to_evaluation_dataset(X) @@ -369,13 +372,13 @@ def predict(self, X): class SelectFirstRegressor(SelectFirstEstimator, RegressorMixin): - def __init__(self, steps, recaller = None): - super(SelectFirstRegressor, self).__init__(steps, recaller) + def __init__(self, steps, controller = None): + super(SelectFirstRegressor, self).__init__(steps, controller) class SelectFirstClassifier(SelectFirstEstimator, ClassifierMixin): - def __init__(self, steps, recaller = None): - super(SelectFirstClassifier, self).__init__(steps, recaller) + def __init__(self, steps, controller = None): + super(SelectFirstClassifier, self).__init__(steps, controller) def predict_proba(self, X): return self._predict(X, "predict_proba")