neural-network - What does bit fail mean?

Question

My neural network has 22 inputs of 5184 values (two digit values, images converted to bytes), and I tried to set 2 output neurons with value 0 or 1, like:

<input data line with 5184 values>
0 1
<input data line with 5184 values>
1 0
<input data line with 5184 values>
.
.
.

From training results :

Epochs            1. Current error: 0.3750000000. Bit fail 33.

What is this bit fail? The documentation says:

The number of fail bits; means the number of output neurons which differ more than the bit fail limit.

How can I have 33 output neurons fail for only 2 output neurons? I imagine this 33 could be from a total of 44 outputs (2 from each of the 22 inputs). But documentation does not confirm this.

Answer 1

数字“33”是在神经网络训练期间您的输出与预期目标输出之间的“差异”之上的数量。这仅表示您的神经网络与所需输出的偏差“太多”了 33 位。请注意，它计算了所有输出，并给出了当前的“错误率”，对您来说是 37.5%。根据文档，标准错误率容差为 0.35，因此假设这一点，在 33*40 = 1320 位输出中对应于 33 位的错误位过多 2.5%。或者至少这是我从这些文档页面中了解到的。

您可能不小心有超过 2 个输出。1320/22 = 60。