def test__data_at_node(self): tree = dt._create_decision_node(self.x, self.labels_train) assert np.all( self.x[self.x[:,2] < 0] == dt._data_at_node(tree, tree.children[0], self.x) ) assert np.all( self.x[self.x[:,2] > 0] == dt._data_at_node(tree, tree.children[1], self.x) )
def test_min_obs_split(self): min_obs = 5 tree = dt._create_decision_node(X_TRAIN, self.labels_train, min_obs_split=min_obs) for desc in tree.descendents(): if len(dt._data_at_node(tree, desc, X_TRAIN)) < min_obs: assert desc.split is None
def test__data_at_node(self): tree = dt._create_decision_node(self.x, self.labels_train) assert np.all(self.x[self.x[:, 2] < 0] == dt._data_at_node( tree, tree.children[0], self.x)) assert np.all(self.x[self.x[:, 2] > 0] == dt._data_at_node( tree, tree.children[1], self.x))