from sklearn.calibration import CalibratedClassifierCV
from sklearn.model_selection import RandomizedSearchCV

pipe_dtr = Pipeline(steps=[('preprocessor', preprocessor),
                           ('clf', DecisionTreeRegressor(random_state=62))])
params_dtr = {
    'clf__max_depth' : np.arange(1,100,5),
    'clf__min_samples_leaf' : [0.01, 0.1, 1]
}
gs_dtr = RandomizedSearchCV(estimator=pipe_dtr,
                    param_distributions=params_dtr,
                    n_iter=25,
                    scoring='roc_auc',
                    cv=5)

gs_dtr.fit(X_train, y_train)

calib_pipe_dtr = Pipeline(steps=[('preprocessor', preprocessor),
                                ('calibrator', CalibratedClassifierCV(gs_dtr.best_estimator_, cv='prefit'))])
calib_pipe_dtr.fit(X_train,y_train)

RuntimeError: classifier has no decision_function or predict_proba method.