decision_tree_binner.py 文件源码

def _recurse_tree(tree, lst, mdlp, node_id=0, depth=0, min_val=np.NINF, max_val=np.PINF):
    left_child = tree.children_left[node_id]
    right_child = tree.children_right[node_id]

    if left_child == sklearn.tree._tree.TREE_LEAF:
        lst.append(((min_val, max_val), tree.value[node_id].flatten().tolist()))
        return
    else:
        if mdlp and _check_mdlp_stop(tree, node_id):
            lst.append(((min_val, max_val), tree.value[node_id].flatten().tolist()))
            return
        _recurse_tree(tree, lst, mdlp, left_child, depth=depth + 1, min_val=min_val, max_val=tree.threshold[node_id])

    if right_child == sklearn.tree._tree.TREE_LEAF:
        lst.append(((min_val, max_val), tree.value[node_id].flatten().tolist()))
        return
    else:
        if mdlp and _check_mdlp_stop(tree, node_id):
            lst.append(((min_val, max_val), tree.value[node_id].flatten().tolist()))
            return
        _recurse_tree(tree, lst, mdlp, right_child, depth=depth + 1, min_val=tree.threshold[node_id], max_val=max_val)