( A, B )---6*30*2---( 1, 0 )( 0, 1 )
让网络的输入只有6个节点，AB训练集各由6张二值化的图片组成，让A的6张图片中共有3个点，B中有1个点.，测试集为二进制的0-63.收敛误差7e-4，比较分类准确率。
| A | B | |||||||||||
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | |
| 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
得到的结果为
| 序号 | 0 | 1 | 2 | 3 | 4 | 5 | 分类 | 分类 | ||||||
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 2 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 3 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 4 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 5 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 6 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 7 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 8 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 9 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 10 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 11 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 12 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 13 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 14 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 15 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 16 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 17 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 18 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 19 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 20 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 21 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 22 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 23 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 24 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 25 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 26 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 27 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 28 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 29 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 30 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 31 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 32 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 33 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 34 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 35 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 36 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 37 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 38 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 39 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 40 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 41 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 42 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 43 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 44 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 45 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 46 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 47 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 48 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | *** | 0 | 1 | * | ||
| 49 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | *** | 0 | 1 | * | ||
| 50 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 51 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 52 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 53 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 54 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 55 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 56 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 57 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 58 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 59 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** | ||
| 60 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | * | 0 | 1 | * | ||
| 61 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | * | 0 | 1 | * | ||
| 62 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | *** | 1 | 1 | *** | ||
| 63 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | *** | 1 | 1 | *** |
13-1的实验做了两次，两次的结果几乎相同
| 48 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | *** | 0 | 1 | * | ||
| 49 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | *** | 0 | 1 | * |
只有第48，49组，两次判断不一致，
将第2次数据画成图，
分类结果很明显，如果在测试图片的第3，4列为00，10被分为B。如果测试图片的3，4列为01，11被分为A。
对比上一次实验，如果B全是0，则测试图片的第3，4列如果不是00，都被分为A。
所以训练集中1的位置对网络的分类有关键影响，有理由认为测试集图片的分类取决于测试图片关键列与训练集关键列的相似度。
