def _train(self):
        m = Model((Document(set(v), type=type) for type, v in self._vectors), weight=BINARY)
        f = sorted(m.features, key=getattr(m, self._method), reverse=True)
        sys.setrecursionlimit(max(len(f) * 2, 1000))
        self._root = self._tree([(v, type) for type, v in self._vectors], features=f)
print the available configurations directly to stdout
dataset/ETHPy150Open clips/pattern/pattern/vector/__init__.py/IGTree._train--crossover with--dataset/ETHPy150Open jut-io/jut-python-tools/jut/config.py/show