这是代码。
from sklearn.neighbors import NearestNeighbors
import numpy as np
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
nbrs = NearestNeighbors(n_neighbors=2, algorithm='ball_tree').fit(X)
distances, indices = nbrs.kneighbors(X)
>indices
>array([[0, 1],[1, 0],[2, 1],[3, 4],[4, 3],[5, 4]])
>distances
>array([[0. , 1. ],[0. , 1. ],[0. , 1.41421356], [0. , 1. ],[0. , 1. ],[0. , 1.41421356]])
我不太了解“指数”和“距离”的形状。我如何理解这些数字的含义？