y - 实际的标签 p - 预测
p = [[1. 1. 1. 1. 1. 1. 0. 1. 1. 1. 1. 1. 1. 1. 0. 1. 0. 1. 1. 0. 1. 0. 0. 1.
1. 1. 1. 0. 0. 1. 1. 1. 1. 1. 1. 0. 0. 1. 0. 0. 1. 1. 1. 0. 1. 1. 0. 1.
0. 0.]]
y=[[1 1 1 1 1 0 1 1 1 1 1 1 1 0 0 1 0 1 1 1 1 0 0 1 1 1 1 0 1 0 1 1 1 1 0 0
0 1 0 0 1 1 1 0 0 0 1 1 1 0]]
a = [[2. 2. 2. 2. 2. 1. 1. 2. 2. 2. 2. 2. 2. 1. 0. 2. 0. 2. 2. 1. 2. 0. 0. 2.
2. 2. 2. 0. 1. 1. 2. 2. 2. 2. 1. 0. 0. 2. 0. 0. 2. 2. 2. 0. 1. 1. 1. 2.
1. 0.]]
a = p + y
mislabeled_indices = np.array(np.where(a == 1))
为什么输出的mislabeled_indices = [[ 0 0 0 0 0 0 0 0 0 0 0]
[ 5 6 13 19 28 29 34 44 45 46 48]]
怎么是(2,x)的列表? 第0行为什么都是0?