def _model_predict_proba(self, X, model_idx=0):
        """Get probability predictions for a model given its index"""

        db_conn = sqlite3.connect(self.db_file)
        curs = db_conn.cursor()
        select_stmt = """select pickled_model
                         from fitted_models
                         where model_idx = ? and fold_idx = ?"""

        # average probs over each n_folds models
        probs = np.zeros((len(X), self._n_classes))
        for fold_idx in xrange(self.n_folds):
            curs.execute(select_stmt, [model_idx, fold_idx])

            res = curs.fetchone()
            model = loads(str(res[0]))

            probs += float(self.n_folds)/model.predict_proba(X)

        db_conn.close()

        return probs
dataset/ETHPy150Open dclambert/pyensemble/ensemble.py/EnsembleSelectionClassifier._model_predict_proba/swapped operands of `/`