r1 |
r2 |
||
<1 |
<1 |
吸引子 |
c |
>1 |
>1 |
排斥子 |
p |
>1 |
<1 |
鞍点 |
a |
<1 |
>1 |
反鞍点 |
fa |
制作一个二分类网络用来分类c和a,通过改变测试集c和a的比例观察网路分类能力的变化,并将得到的数据拟合成数学表达式。
训练集的比例c:a=1:1,
测试集c和a的比例为x:y.
让x:y的比例分别为0:10,1:9,2:8,3:7,4:6,5:5,6:4,7:3,8:2,9:1,10:0。
实验过程
二分类吸引子和鞍点
制作一个4*4*2的网络向这个的左侧输入吸引子,并让左侧网络向1,0收敛;向右侧网络输入鞍点让右侧向0,1收敛,并让4*4*2部分权重共享,前面大量实验表明这种效果相当于将两个弹性系数为k1,k2的弹簧并联成一个弹性系数为k的弹簧,并且让k1=k2=k/2的过程。
这个网络的收敛标准是
if (Math.abs(f2[0]-y[0])< δ && Math.abs(f2[1]-y[1])< δ )
因为对应每个收敛标准δ都有一个特征的迭代次数n与之对应因此可以用迭代次数曲线n(δ)来评价网络性能。
本文尝试了δ从0.5到1e-6在内的36个值.
具体进样顺序 |
|||
进样顺序 |
迭代次数 |
||
δ=0.5 |
|||
c |
1 |
判断是否达到收敛 |
|
a |
2 |
判断是否达到收敛 |
|
梯度下降 |
|||
c |
3 |
判断是否达到收敛 |
|
a |
4 |
判断是否达到收敛 |
|
梯度下降 |
|||
…… |
|||
达到收敛标准测量准确率,记录迭代次数,将这个过程重复199次 |
|||
δ=0.4 |
|||
… |
|||
δ=1e-6 |
将这个网络简写成
d2(c,a)-4-4-2-(2*k),k∈{0,1}
得到的数据
以第一组为例
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0 |
c |
||||||
10 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.499549 |
0.516406 |
181.2261 |
1 |
0.5 |
1.984925 |
410 |
0.006833 |
1 |
0.608557 |
0.395061 |
4200.583 |
0.972752 |
0.4 |
10.57286 |
2119 |
0.035317 |
1 |
0.719274 |
0.285924 |
4900.789 |
0.940176 |
0.3 |
9.477387 |
1886 |
0.031433 |
0.984985 |
0.81995 |
0.185329 |
5614.688 |
0.919266 |
0.2 |
10.49246 |
2088 |
0.0348 |
0.988989 |
0.913052 |
0.088778 |
6392.407 |
0.897858 |
0.1 |
11.28141 |
2260 |
0.037667 |
0.967968 |
0.991559 |
0.008561 |
9046.377 |
0.860297 |
0.01 |
16.69347 |
3323 |
0.055383 |
0.957958 |
0.999172 |
8.40E-04 |
13557.47 |
0.845785 |
0.001 |
23.15075 |
4607 |
0.076783 |
0.947948 |
0.999918 |
8.24E-05 |
22123.3 |
0.841002 |
1.00E-04 |
38.13065 |
7589 |
0.126483 |
0.941942 |
0.999927 |
7.41E-05 |
22794.29 |
0.838778 |
9.00E-05 |
39.96482 |
7953 |
0.13255 |
0.923924 |
0.999935 |
6.59E-05 |
23001.94 |
0.842139 |
8.00E-05 |
39.59799 |
7880 |
0.131333 |
0.925926 |
0.999944 |
5.69E-05 |
23585.63 |
0.835926 |
7.00E-05 |
40.05528 |
7972 |
0.132867 |
0.918919 |
0.99995 |
5.01E-05 |
25008.55 |
0.844488 |
6.00E-05 |
42.19095 |
8396 |
0.139933 |
0.933934 |
0.999959 |
4.14E-05 |
25913.07 |
0.843602 |
5.00E-05 |
44.65327 |
8901 |
0.14835 |
0.930931 |
0.999967 |
3.33E-05 |
27440.44 |
0.840413 |
4.00E-05 |
47.28141 |
9409 |
0.156817 |
0.935936 |
0.999976 |
2.44E-05 |
29798.31 |
0.832471 |
3.00E-05 |
51.21106 |
10206 |
0.1701 |
0.937938 |
0.999984 |
1.57E-05 |
32360.2 |
0.830001 |
2.00E-05 |
55.69849 |
11084 |
0.184733 |
0.914915 |
0.999992 |
8.29E-06 |
40696.32 |
0.828668 |
1.00E-05 |
68.1407 |
13560 |
0.226 |
0.916917 |
0.999993 |
7.35E-06 |
40860.31 |
0.820514 |
9.00E-06 |
69.38693 |
13808 |
0.230133 |
0.905906 |
0.999993 |
6.54E-06 |
43086.26 |
0.822501 |
8.00E-06 |
72.56784 |
14441 |
0.240683 |
0.90991 |
0.999994 |
5.59E-06 |
45369.46 |
0.817717 |
7.00E-06 |
76.98492 |
15352 |
0.255867 |
0.91992 |
0.999995 |
4.88E-06 |
48723.63 |
0.817586 |
6.00E-06 |
83.66834 |
16651 |
0.277517 |
0.908909 |
0.999996 |
4.11E-06 |
51922.08 |
0.810378 |
5.00E-06 |
86.40201 |
17210 |
0.286833 |
0.894895 |
0.999997 |
3.24E-06 |
57409.06 |
0.805051 |
4.00E-06 |
96.86935 |
19277 |
0.321283 |
0.886887 |
0.999998 |
2.37E-06 |
67244.38 |
0.787682 |
3.00E-06 |
113.3116 |
22549 |
0.375817 |
0.883884 |
0.999998 |
1.57E-06 |
87439.24 |
0.763432 |
2.00E-06 |
147.5025 |
29370 |
0.4895 |
0.873874 |
0.999999 |
7.30E-07 |
135984.2 |
0.724051 |
1.00E-06 |
228.2261 |
45417 |
0.75695 |
0.874875 |
这个网络的测试集c与a的比例是0:1,也就全是a。
将得到的平均准确率画成图
网络的准确率没有随着迭代的增加而增加,将1e-5到1e-6的平均准确率平均为0.799758。
其他的数据
a |
1 |
0.9 |
0.8 |
0.7 |
0.6 |
0.5 |
0.4 |
0.3 |
0.2 |
0.1 |
0 |
|
平均准确率p-ave |
||||||||||||
c |
δ |
0 |
0.1 |
0.2 |
0.3 |
0.4 |
0.5 |
0.6 |
0.7 |
0.8 |
0.9 |
1 |
0.5 |
1 |
0.899814 |
0.800947 |
0.699901 |
0.600656 |
0.500707 |
0.401804 |
0.299521 |
0.201734 |
0.102912 |
6.09E-04 |
|
0.4 |
0.972752 |
0.960589 |
0.947369 |
0.93407 |
0.919779 |
0.907405 |
0.89401 |
0.8816 |
0.863985 |
0.855051 |
0.84492 |
|
0.3 |
0.940176 |
0.928129 |
0.920393 |
0.913049 |
0.904261 |
0.895856 |
0.889005 |
0.876962 |
0.871897 |
0.864402 |
0.856746 |
|
0.2 |
0.919266 |
0.908833 |
0.902908 |
0.895871 |
0.890448 |
0.88653 |
0.88076 |
0.874825 |
0.868648 |
0.860725 |
0.857264 |
|
0.1 |
0.897858 |
0.890167 |
0.884533 |
0.882762 |
0.879337 |
0.874789 |
0.87154 |
0.865982 |
0.862174 |
0.856802 |
0.857128 |
|
0.01 |
0.860297 |
0.858492 |
0.861545 |
0.861354 |
0.860916 |
0.863416 |
0.86322 |
0.863959 |
0.863783 |
0.865841 |
0.866193 |
|
0.001 |
0.845785 |
0.849136 |
0.853804 |
0.856238 |
0.857425 |
0.862772 |
0.865655 |
0.868713 |
0.873124 |
0.877003 |
0.876867 |
|
1.00E-04 |
0.841002 |
0.847118 |
0.853859 |
0.858099 |
0.862878 |
0.868139 |
0.872898 |
0.877858 |
0.884749 |
0.886022 |
0.893491 |
|
9.00E-05 |
0.838778 |
0.847712 |
0.855489 |
0.85398 |
0.863869 |
0.867088 |
0.874558 |
0.878406 |
0.883321 |
0.887737 |
0.896248 |
|
8.00E-05 |
0.842139 |
0.84985 |
0.850147 |
0.857531 |
0.862667 |
0.869241 |
0.872938 |
0.879306 |
0.885262 |
0.888532 |
0.893949 |
|
7.00E-05 |
0.835926 |
0.843215 |
0.853391 |
0.859095 |
0.861877 |
0.869422 |
0.874804 |
0.880363 |
0.88493 |
0.887994 |
0.895368 |
|
6.00E-05 |
0.844488 |
0.843839 |
0.850861 |
0.858331 |
0.864664 |
0.869216 |
0.874382 |
0.87991 |
0.886756 |
0.889281 |
0.897646 |
|
5.00E-05 |
0.843602 |
0.838819 |
0.851419 |
0.855725 |
0.863321 |
0.868698 |
0.876173 |
0.88232 |
0.887304 |
0.890514 |
0.897335 |
|
4.00E-05 |
0.840413 |
0.84147 |
0.850931 |
0.856711 |
0.864135 |
0.869442 |
0.876485 |
0.882244 |
0.886736 |
0.896303 |
0.901082 |
|
3.00E-05 |
0.832471 |
0.846424 |
0.849905 |
0.8591 |
0.864261 |
0.869251 |
0.877858 |
0.884784 |
0.889709 |
0.896992 |
0.901761 |
|
2.00E-05 |
0.830001 |
0.838784 |
0.848864 |
0.856565 |
0.864085 |
0.871007 |
0.877843 |
0.8857 |
0.892244 |
0.903004 |
0.909412 |
|
1.00E-05 |
0.828668 |
0.837451 |
0.846173 |
0.854623 |
0.862948 |
0.872123 |
0.881937 |
0.890539 |
0.89988 |
0.909452 |
0.918768 |
|
9.00E-06 |
0.820514 |
0.829664 |
0.845036 |
0.855076 |
0.864312 |
0.871153 |
0.882174 |
0.892093 |
0.901535 |
0.910735 |
0.919377 |
|
8.00E-06 |
0.822501 |
0.832969 |
0.840952 |
0.853502 |
0.865111 |
0.870458 |
0.882782 |
0.892833 |
0.902294 |
0.910327 |
0.922888 |
|
7.00E-06 |
0.817717 |
0.832692 |
0.8407 |
0.853467 |
0.859422 |
0.872355 |
0.883391 |
0.892898 |
0.90414 |
0.91329 |
0.925745 |
|
6.00E-06 |
0.817586 |
0.823265 |
0.843416 |
0.851927 |
0.865222 |
0.872234 |
0.882063 |
0.894608 |
0.904774 |
0.915996 |
0.931062 |
|
5.00E-06 |
0.810378 |
0.824458 |
0.835816 |
0.846429 |
0.860388 |
0.869437 |
0.884145 |
0.89579 |
0.90825 |
0.920347 |
0.933843 |
|
4.00E-06 |
0.805051 |
0.811706 |
0.82903 |
0.843195 |
0.857068 |
0.871218 |
0.884181 |
0.897878 |
0.909331 |
0.926902 |
0.938179 |
|
3.00E-06 |
0.787682 |
0.810997 |
0.822259 |
0.836621 |
0.855494 |
0.87069 |
0.888698 |
0.902184 |
0.917566 |
0.93419 |
0.95077 |
|
2.00E-06 |
0.763432 |
0.794402 |
0.805494 |
0.824241 |
0.845353 |
0.865046 |
0.883803 |
0.905192 |
0.927214 |
0.946389 |
0.965694 |
|
1.00E-06 |
0.724051 |
0.754337 |
0.783356 |
0.806228 |
0.835685 |
0.852511 |
0.884135 |
0.911686 |
0.934241 |
0.959251 |
0.985453 |
|
0.799758 |
0.815194 |
0.829223 |
0.842531 |
0.8571 |
0.868722 |
0.883731 |
0.89757 |
0.910922 |
0.924688 |
0.939178 |
当c:a=0:1时网络的准确率是79.9758%当c:a=1:0时准确率是0.939178。
也就是当c与a是1:1进样的时候可以识别出79.9758%的a,可以识别出93.9178%的c。画成图
如果用pc和pa表示测试集中c与a的比例则
d2(c,a)-4-4-2-(2*k),k∈{0,1}的平均准确率的表达式为
a |
1 |
0.9 |
0.8 |
0.7 |
0.6 |
0.5 |
0.4 |
0.3 |
0.2 |
0.1 |
0 |
|
c |
|
0 |
0.1 |
0.2 |
0.3 |
0.4 |
0.5 |
0.6 |
0.7 |
0.8 |
0.9 |
1 |
平均准确率p-ave |
实测值 |
0.799758 |
0.815194 |
0.829223 |
0.842531 |
0.8571 |
0.868722 |
0.883731 |
0.89757 |
0.910922 |
0.924688 |
0.939178 |
计算值 |
0.799758 |
0.8137 |
0.827642 |
0.841584 |
0.855526 |
0.869468 |
0.88341 |
0.897352 |
0.911294 |
0.925236 |
0.939178 |
将实测值和计算值画成图
图像是高度重合的。
实验参数
学习率 0.1 |
权重初始化方式 |
Random rand1 =new Random(); |
int ti1=rand1.nextInt(98)+1; tw[a][b]=xx*((double)ti1/100); |
训练集 |
0.5 |
c |
|||||||
|
0.5 |
a |
|||||||
测试集 |
0 |
c |
|||||||
10 |
a |
||||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
|
0.499549 |
0.516406 |
181.2261 |
1 |
0.5 |
1.984925 |
410 |
0.006833 |
1 |
|
0.608557 |
0.395061 |
4200.583 |
0.972752 |
0.4 |
10.57286 |
2119 |
0.035317 |
1 |
|
0.719274 |
0.285924 |
4900.789 |
0.940176 |
0.3 |
9.477387 |
1886 |
0.031433 |
0.984985 |
|
0.81995 |
0.185329 |
5614.688 |
0.919266 |
0.2 |
10.49246 |
2088 |
0.0348 |
0.988989 |
|
0.913052 |
0.088778 |
6392.407 |
0.897858 |
0.1 |
11.28141 |
2260 |
0.037667 |
0.967968 |
|
0.991559 |
0.008561 |
9046.377 |
0.860297 |
0.01 |
16.69347 |
3323 |
0.055383 |
0.957958 |
|
0.999172 |
8.40E-04 |
13557.47 |
0.845785 |
0.001 |
23.15075 |
4607 |
0.076783 |
0.947948 |
|
0.999918 |
8.24E-05 |
22123.3 |
0.841002 |
1.00E-04 |
38.13065 |
7589 |
0.126483 |
0.941942 |
|
0.999927 |
7.41E-05 |
22794.29 |
0.838778 |
9.00E-05 |
39.96482 |
7953 |
0.13255 |
0.923924 |
|
0.999935 |
6.59E-05 |
23001.94 |
0.842139 |
8.00E-05 |
39.59799 |
7880 |
0.131333 |
0.925926 |
|
0.999944 |
5.69E-05 |
23585.63 |
0.835926 |
7.00E-05 |
40.05528 |
7972 |
0.132867 |
0.918919 |
|
0.99995 |
5.01E-05 |
25008.55 |
0.844488 |
6.00E-05 |
42.19095 |
8396 |
0.139933 |
0.933934 |
|
0.999959 |
4.14E-05 |
25913.07 |
0.843602 |
5.00E-05 |
44.65327 |
8901 |
0.14835 |
0.930931 |
|
0.999967 |
3.33E-05 |
27440.44 |
0.840413 |
4.00E-05 |
47.28141 |
9409 |
0.156817 |
0.935936 |
|
0.999976 |
2.44E-05 |
29798.31 |
0.832471 |
3.00E-05 |
51.21106 |
10206 |
0.1701 |
0.937938 |
|
0.999984 |
1.57E-05 |
32360.2 |
0.830001 |
2.00E-05 |
55.69849 |
11084 |
0.184733 |
0.914915 |
|
0.999992 |
8.29E-06 |
40696.32 |
0.828668 |
1.00E-05 |
68.1407 |
13560 |
0.226 |
0.916917 |
|
0.999993 |
7.35E-06 |
40860.31 |
0.820514 |
9.00E-06 |
69.38693 |
13808 |
0.230133 |
0.905906 |
|
0.999993 |
6.54E-06 |
43086.26 |
0.822501 |
8.00E-06 |
72.56784 |
14441 |
0.240683 |
0.90991 |
|
0.999994 |
5.59E-06 |
45369.46 |
0.817717 |
7.00E-06 |
76.98492 |
15352 |
0.255867 |
0.91992 |
|
0.999995 |
4.88E-06 |
48723.63 |
0.817586 |
6.00E-06 |
83.66834 |
16651 |
0.277517 |
0.908909 |
|
0.999996 |
4.11E-06 |
51922.08 |
0.810378 |
5.00E-06 |
86.40201 |
17210 |
0.286833 |
0.894895 |
|
0.999997 |
3.24E-06 |
57409.06 |
0.805051 |
4.00E-06 |
96.86935 |
19277 |
0.321283 |
0.886887 |
|
0.999998 |
2.37E-06 |
67244.38 |
0.787682 |
3.00E-06 |
113.3116 |
22549 |
0.375817 |
0.883884 |
|
0.999998 |
1.57E-06 |
87439.24 |
0.763432 |
2.00E-06 |
147.5025 |
29370 |
0.4895 |
0.873874 |
|
0.999999 |
7.30E-07 |
135984.2 |
0.724051 |
1.00E-06 |
228.2261 |
45417 |
0.75695 |
0.874875 |
|
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.1 |
c |
||||||
0.9 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.499559 |
0.515984 |
182.5829 |
0.899814 |
0.5 |
2.18593 |
435 |
0.00725 |
0.923924 |
0.606113 |
0.398241 |
4202.759 |
0.960589 |
0.4 |
10.96482 |
2185 |
0.036417 |
0.984985 |
0.720845 |
0.28548 |
4989.995 |
0.928129 |
0.3 |
10.06533 |
2011 |
0.033517 |
0.968969 |
0.820824 |
0.185466 |
5666.899 |
0.908833 |
0.2 |
11.31658 |
2252 |
0.037533 |
0.962963 |
0.913407 |
0.088863 |
6468.276 |
0.890167 |
0.1 |
13.35176 |
2669 |
0.044483 |
0.943944 |
0.991783 |
0.008418 |
9085.854 |
0.858492 |
0.01 |
19.30653 |
3871 |
0.064517 |
0.944945 |
0.999179 |
8.34E-04 |
13474.49 |
0.849136 |
0.001 |
24.70854 |
4926 |
0.0821 |
0.915916 |
0.999917 |
8.33E-05 |
21834.68 |
0.847118 |
1.00E-04 |
39.28141 |
7832 |
0.130533 |
0.923924 |
0.999924 |
7.67E-05 |
22594.16 |
0.847712 |
9.00E-05 |
41.66834 |
8300 |
0.138333 |
0.912913 |
0.999936 |
6.48E-05 |
23324.59 |
0.84985 |
8.00E-05 |
41.62814 |
8286 |
0.1381 |
0.93994 |
0.999943 |
5.73E-05 |
24021.38 |
0.843215 |
7.00E-05 |
42.65829 |
8489 |
0.141483 |
0.928929 |
0.999951 |
4.97E-05 |
24449.18 |
0.843839 |
6.00E-05 |
43.9598 |
8756 |
0.145933 |
0.911912 |
0.99996 |
4.07E-05 |
25922.65 |
0.838819 |
5.00E-05 |
46.63317 |
9281 |
0.154683 |
0.913914 |
0.999967 |
3.31E-05 |
27721.9 |
0.84147 |
4.00E-05 |
49.60804 |
9880 |
0.164667 |
0.923924 |
0.999976 |
2.44E-05 |
29257.83 |
0.846424 |
3.00E-05 |
52.44221 |
10444 |
0.174067 |
0.921922 |
0.999984 |
1.65E-05 |
33433.06 |
0.838784 |
2.00E-05 |
59.96482 |
11933 |
0.198883 |
0.910911 |
0.999992 |
7.97E-06 |
40294.68 |
0.837451 |
1.00E-05 |
70.13568 |
13973 |
0.232883 |
0.916917 |
0.999993 |
7.14E-06 |
41447.01 |
0.829664 |
9.00E-06 |
72.50754 |
14429 |
0.240483 |
0.920921 |
0.999994 |
6.32E-06 |
43436.44 |
0.832969 |
8.00E-06 |
77.01005 |
15325 |
0.255417 |
0.912913 |
0.999994 |
5.67E-06 |
45515.5 |
0.832692 |
7.00E-06 |
79.71357 |
15863 |
0.264383 |
0.903904 |
0.999995 |
4.85E-06 |
48621.58 |
0.823265 |
6.00E-06 |
85.1809 |
16967 |
0.282783 |
0.908909 |
0.999996 |
4.06E-06 |
52096.44 |
0.824458 |
5.00E-06 |
90.80905 |
18087 |
0.30145 |
0.915916 |
0.999997 |
3.18E-06 |
56452.7 |
0.811706 |
4.00E-06 |
98.50754 |
19614 |
0.3269 |
0.906907 |
0.999998 |
2.42E-06 |
69077.34 |
0.810997 |
3.00E-06 |
124.4874 |
24781 |
0.413017 |
0.896897 |
0.999998 |
1.56E-06 |
89547.6 |
0.794402 |
2.00E-06 |
157.2312 |
31290 |
0.5215 |
0.886887 |
0.999999 |
7.79E-07 |
137262.4 |
0.754337 |
1.00E-06 |
239.2613 |
47613 |
0.79355 |
0.886887 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.2 |
c |
||||||
0.8 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.499574 |
0.516447 |
180.3618 |
0.800947 |
0.5 |
2.105528 |
422 |
0.007033 |
0.825826 |
0.60819 |
0.396577 |
4089.965 |
0.947369 |
0.4 |
11.37688 |
2266 |
0.037767 |
0.974975 |
0.719785 |
0.284101 |
5063.613 |
0.920393 |
0.3 |
10.51256 |
2093 |
0.034883 |
0.95996 |
0.821756 |
0.183251 |
5692.839 |
0.902908 |
0.2 |
11.97487 |
2383 |
0.039717 |
0.941942 |
0.912977 |
0.089543 |
6441.352 |
0.884533 |
0.1 |
12.61307 |
2534 |
0.042233 |
0.940941 |
0.991778 |
0.008391 |
9114.005 |
0.861545 |
0.01 |
17.1608 |
3415 |
0.056917 |
0.927928 |
0.999187 |
8.34E-04 |
13574.83 |
0.853804 |
0.001 |
24.68844 |
4938 |
0.0823 |
0.92993 |
0.99992 |
8.14E-05 |
21810.96 |
0.853859 |
1.00E-04 |
38.47739 |
7673 |
0.127883 |
0.904905 |
0.999925 |
7.54E-05 |
22252.22 |
0.855489 |
9.00E-05 |
39.37186 |
7835 |
0.130583 |
0.91992 |
0.999935 |
6.59E-05 |
22982.17 |
0.850147 |
8.00E-05 |
40.54774 |
8069 |
0.134483 |
0.908909 |
0.999942 |
5.82E-05 |
24360.98 |
0.853391 |
7.00E-05 |
42.86432 |
8545 |
0.142417 |
0.925926 |
0.99995 |
5.06E-05 |
24677.08 |
0.850861 |
6.00E-05 |
43.68342 |
8712 |
0.1452 |
0.90991 |
0.99996 |
4.02E-05 |
25614.11 |
0.851419 |
5.00E-05 |
44.96482 |
8948 |
0.149133 |
0.918919 |
0.999967 |
3.31E-05 |
28052.94 |
0.850931 |
4.00E-05 |
50.21608 |
9993 |
0.16655 |
0.908909 |
0.999976 |
2.46E-05 |
29987.39 |
0.849905 |
3.00E-05 |
55.91457 |
11128 |
0.185467 |
0.910911 |
0.999984 |
1.66E-05 |
32564.42 |
0.848864 |
2.00E-05 |
57.42714 |
11428 |
0.190467 |
0.918919 |
0.999992 |
8.37E-06 |
40750.95 |
0.846173 |
1.00E-05 |
72.9397 |
14516 |
0.241933 |
0.906907 |
0.999993 |
7.16E-06 |
41606.82 |
0.845036 |
9.00E-06 |
73.82915 |
14699 |
0.244983 |
0.90991 |
0.999994 |
6.30E-06 |
43684.39 |
0.840952 |
8.00E-06 |
76.90452 |
15312 |
0.2552 |
0.914915 |
0.999994 |
5.66E-06 |
47273.61 |
0.8407 |
7.00E-06 |
84.40704 |
16798 |
0.279967 |
0.903904 |
0.999995 |
4.93E-06 |
49040.06 |
0.843416 |
6.00E-06 |
86.94472 |
17314 |
0.288567 |
0.908909 |
0.999996 |
4.00E-06 |
52722.31 |
0.835816 |
5.00E-06 |
93.31658 |
18570 |
0.3095 |
0.913914 |
0.999997 |
3.14E-06 |
58800.85 |
0.82903 |
4.00E-06 |
103.8492 |
20674 |
0.344567 |
0.905906 |
0.999998 |
2.40E-06 |
67739.11 |
0.822259 |
3.00E-06 |
120.4271 |
23965 |
0.399417 |
0.891892 |
0.999998 |
1.56E-06 |
89028.13 |
0.805494 |
2.00E-06 |
155.598 |
30964 |
0.516067 |
0.888889 |
0.999999 |
7.53E-07 |
133418.5 |
0.783356 |
1.00E-06 |
235.794 |
46923 |
0.78205 |
0.915916 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.3 |
c |
||||||
0.7 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.499563 |
0.516764 |
181.0653 |
0.699901 |
0.5 |
2.326633 |
464 |
0.007733 |
0.735736 |
0.598109 |
0.405997 |
4276.201 |
0.93407 |
0.4 |
10.8191 |
2154 |
0.0359 |
0.965966 |
0.719868 |
0.285054 |
4898.859 |
0.913049 |
0.3 |
10.84422 |
2160 |
0.036 |
0.942943 |
0.819455 |
0.184858 |
5667.925 |
0.895871 |
0.2 |
11.59296 |
2324 |
0.038733 |
0.942943 |
0.91238 |
0.089912 |
6447.111 |
0.882762 |
0.1 |
12.84925 |
2558 |
0.042633 |
0.921922 |
0.991728 |
0.008504 |
9021.392 |
0.861354 |
0.01 |
18.29648 |
3642 |
0.0607 |
0.915916 |
0.999179 |
8.39E-04 |
13362.78 |
0.856238 |
0.001 |
25.00503 |
4976 |
0.082933 |
0.912913 |
0.999918 |
8.29E-05 |
21841.37 |
0.858099 |
1.00E-04 |
39.49246 |
7860 |
0.131 |
0.907908 |
0.999925 |
7.58E-05 |
22117.96 |
0.85398 |
9.00E-05 |
39.78894 |
7918 |
0.131967 |
0.910911 |
0.999935 |
6.59E-05 |
23374.83 |
0.857531 |
8.00E-05 |
42.23116 |
8410 |
0.140167 |
0.908909 |
0.999943 |
5.73E-05 |
24088.55 |
0.859095 |
7.00E-05 |
43.53769 |
8673 |
0.14455 |
0.918919 |
0.999951 |
4.99E-05 |
24232.19 |
0.858331 |
6.00E-05 |
42.79899 |
8518 |
0.141967 |
0.912913 |
0.999959 |
4.10E-05 |
25768.17 |
0.855725 |
5.00E-05 |
46.08543 |
9188 |
0.153133 |
0.913914 |
0.999968 |
3.27E-05 |
27126.85 |
0.856711 |
4.00E-05 |
50.10553 |
9972 |
0.1662 |
0.915916 |
0.999975 |
2.52E-05 |
29311.8 |
0.8591 |
3.00E-05 |
53.26131 |
10600 |
0.176667 |
0.907908 |
0.999984 |
1.64E-05 |
33121.41 |
0.856565 |
2.00E-05 |
58.23116 |
11588 |
0.193133 |
0.906907 |
0.999992 |
7.99E-06 |
40591.23 |
0.854623 |
1.00E-05 |
-683.337 |
-135968 |
-2.26613 |
0.915916 |
0.999992 |
7.57E-06 |
42242.42 |
0.855076 |
9.00E-06 |
74.38693 |
14813 |
0.246883 |
0.911912 |
0.999993 |
6.59E-06 |
43143.39 |
0.853502 |
8.00E-06 |
76.71357 |
15274 |
0.254567 |
0.901902 |
0.999994 |
5.78E-06 |
44787.41 |
0.853467 |
7.00E-06 |
79.02513 |
15734 |
0.262233 |
0.912913 |
0.999995 |
4.78E-06 |
48122.64 |
0.851927 |
6.00E-06 |
85.11558 |
16954 |
0.282567 |
0.908909 |
0.999996 |
4.01E-06 |
52609.96 |
0.846429 |
5.00E-06 |
92.59799 |
18427 |
0.307117 |
0.8999 |
0.999997 |
3.24E-06 |
55338.42 |
0.843195 |
4.00E-06 |
98.55779 |
19625 |
0.327083 |
0.904905 |
0.999998 |
2.34E-06 |
66951.1 |
0.836621 |
3.00E-06 |
117.8543 |
23454 |
0.3909 |
0.905906 |
0.999998 |
1.56E-06 |
89347.83 |
0.824241 |
2.00E-06 |
156.9146 |
31236 |
0.5206 |
0.904905 |
0.999999 |
7.51E-07 |
135976.4 |
0.806228 |
1.00E-06 |
240.4925 |
47867 |
0.797783 |
0.8999 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.4 |
c |
||||||
0.6 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.49958 |
0.51682 |
179.0151 |
0.600656 |
0.5 |
2.261307 |
451 |
0.007517 |
0.637638 |
0.600314 |
0.403284 |
4147.814 |
0.919779 |
0.4 |
9.869347 |
1967 |
0.032783 |
0.955956 |
0.720156 |
0.283361 |
4858.015 |
0.904261 |
0.3 |
9.979899 |
1987 |
0.033117 |
0.936937 |
0.8191 |
0.184599 |
5643.131 |
0.890448 |
0.2 |
11.17085 |
2232 |
0.0372 |
0.937938 |
0.914373 |
0.088719 |
6489.02 |
0.879337 |
0.1 |
13.38693 |
2672 |
0.044533 |
0.910911 |
0.991696 |
0.008514 |
9133.513 |
0.860916 |
0.01 |
17.74372 |
3532 |
0.058867 |
0.901902 |
0.999189 |
8.28E-04 |
13622.89 |
0.857425 |
0.001 |
25.07538 |
5000 |
0.083333 |
0.893894 |
0.999918 |
8.26E-05 |
22021.09 |
0.862878 |
1.00E-04 |
40.02513 |
7973 |
0.132883 |
0.901902 |
0.999927 |
7.37E-05 |
22306.3 |
0.863869 |
9.00E-05 |
40.60302 |
8080 |
0.134667 |
0.90991 |
0.999935 |
6.60E-05 |
22824.64 |
0.862667 |
8.00E-05 |
41.44724 |
8256 |
0.1376 |
0.900901 |
0.999942 |
5.83E-05 |
23730.49 |
0.861877 |
7.00E-05 |
42.99497 |
8556 |
0.1426 |
0.906907 |
0.999951 |
4.98E-05 |
24605.66 |
0.864664 |
6.00E-05 |
43.64824 |
8699 |
0.144983 |
0.908909 |
0.999959 |
4.14E-05 |
25657.53 |
0.863321 |
5.00E-05 |
45.70352 |
9095 |
0.151583 |
0.903904 |
0.999968 |
3.28E-05 |
26791.41 |
0.864135 |
4.00E-05 |
47.70352 |
9501 |
0.15835 |
0.904905 |
0.999975 |
2.49E-05 |
29539.54 |
0.864261 |
3.00E-05 |
52.92462 |
10549 |
0.175817 |
0.911912 |
0.999984 |
1.63E-05 |
33273.41 |
0.864085 |
2.00E-05 |
59.76382 |
11893 |
0.198217 |
0.910911 |
0.999992 |
8.12E-06 |
39976.45 |
0.862948 |
1.00E-05 |
71.15075 |
14167 |
0.236117 |
0.903904 |
0.999993 |
7.32E-06 |
41968.86 |
0.864312 |
9.00E-06 |
74.44221 |
14814 |
0.2469 |
0.910911 |
0.999993 |
6.54E-06 |
43223.41 |
0.865111 |
8.00E-06 |
76.43719 |
15219 |
0.25365 |
0.917918 |
0.999994 |
5.61E-06 |
45152.72 |
0.859422 |
7.00E-06 |
80.22613 |
15973 |
0.266217 |
0.914915 |
0.999995 |
4.88E-06 |
48118.48 |
0.865222 |
6.00E-06 |
84.86432 |
16888 |
0.281467 |
0.911912 |
0.999996 |
4.01E-06 |
52712.63 |
0.860388 |
5.00E-06 |
92.54774 |
18424 |
0.307067 |
0.903904 |
0.999997 |
3.13E-06 |
58584.19 |
0.857068 |
4.00E-06 |
103.7337 |
20659 |
0.344317 |
0.907908 |
0.999998 |
2.38E-06 |
68493.08 |
0.855494 |
3.00E-06 |
121.3367 |
24154 |
0.402567 |
0.907908 |
0.999998 |
1.53E-06 |
90109.07 |
0.845353 |
2.00E-06 |
158.4422 |
31530 |
0.5255 |
0.920921 |
0.999999 |
7.59E-07 |
138970.9 |
0.835685 |
1.00E-06 |
244.603 |
48679 |
0.811317 |
0.902903 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.5 |
c |
||||||
0.5 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.499569 |
0.516438 |
180.5829 |
0.500707 |
0.5 |
2.130653 |
440 |
0.007333 |
0.62963 |
0.603337 |
0.401501 |
4137.648 |
0.907405 |
0.4 |
8.809045 |
1785 |
0.02975 |
0.950951 |
0.719646 |
0.285824 |
4989.814 |
0.895856 |
0.3 |
10.12563 |
2015 |
0.033583 |
0.926927 |
0.820554 |
0.184931 |
5547.925 |
0.88653 |
0.2 |
11.10553 |
2223 |
0.03705 |
0.920921 |
0.91342 |
0.090681 |
6274.035 |
0.874789 |
0.1 |
12.07035 |
2418 |
0.0403 |
0.906907 |
0.991693 |
0.008545 |
9126.075 |
0.863416 |
0.01 |
19.40201 |
3885 |
0.06475 |
0.896897 |
0.999186 |
8.31E-04 |
13454.45 |
0.862772 |
0.001 |
24.82915 |
4952 |
0.082533 |
0.897898 |
0.999919 |
8.20E-05 |
21767.77 |
0.868139 |
1.00E-04 |
38.61809 |
7686 |
0.1281 |
0.901902 |
0.999927 |
7.38E-05 |
22688.33 |
0.867088 |
9.00E-05 |
40.18593 |
8005 |
0.133417 |
0.900901 |
0.999934 |
6.63E-05 |
23244.96 |
0.869241 |
8.00E-05 |
41.75377 |
8309 |
0.138483 |
0.908909 |
0.999942 |
5.85E-05 |
24121.77 |
0.869422 |
7.00E-05 |
43.72864 |
8720 |
0.145333 |
0.904905 |
0.999951 |
4.99E-05 |
24631.73 |
0.869216 |
6.00E-05 |
43.59799 |
8678 |
0.144633 |
0.903904 |
0.999959 |
4.08E-05 |
26436.8 |
0.868698 |
5.00E-05 |
47.10553 |
9375 |
0.15625 |
0.903904 |
0.999967 |
3.28E-05 |
27315.33 |
0.869442 |
4.00E-05 |
48.9397 |
9748 |
0.162467 |
0.906907 |
0.999975 |
2.47E-05 |
29643.38 |
0.869251 |
3.00E-05 |
52.57286 |
10464 |
0.1744 |
0.902903 |
0.999984 |
1.62E-05 |
32292.43 |
0.871007 |
2.00E-05 |
57.10553 |
11374 |
0.189567 |
0.90991 |
0.999992 |
8.19E-06 |
41034.54 |
0.872123 |
1.00E-05 |
72.9799 |
14523 |
0.24205 |
0.904905 |
0.999993 |
7.21E-06 |
41606.16 |
0.871153 |
9.00E-06 |
72.73367 |
14476 |
0.241267 |
0.910911 |
0.999994 |
6.43E-06 |
44033.12 |
0.870458 |
8.00E-06 |
78.95477 |
15721 |
0.262017 |
0.922923 |
0.999994 |
5.58E-06 |
46175.42 |
0.872355 |
7.00E-06 |
80.93467 |
16114 |
0.268567 |
0.916917 |
0.999995 |
4.84E-06 |
48331.53 |
0.872234 |
6.00E-06 |
85.45226 |
17005 |
0.283417 |
0.910911 |
0.999996 |
3.92E-06 |
51810.29 |
0.869437 |
5.00E-06 |
90.86935 |
18086 |
0.301433 |
0.907908 |
0.999997 |
3.20E-06 |
57527.16 |
0.871218 |
4.00E-06 |
100.7487 |
20049 |
0.33415 |
0.906907 |
0.999998 |
2.36E-06 |
66458.26 |
0.87069 |
3.00E-06 |
116.598 |
23204 |
0.386733 |
0.910911 |
0.999998 |
1.53E-06 |
90787.31 |
0.865046 |
2.00E-06 |
159.1608 |
31681 |
0.528017 |
0.917918 |
0.999999 |
7.22E-07 |
135588.1 |
0.852511 |
1.00E-06 |
237.0905 |
47182 |
0.786367 |
0.918919 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.6 |
c |
||||||
0.4 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.49954 |
0.51599 |
179.8894 |
0.401804 |
0.5 |
2.316583 |
461 |
0.007683 |
0.556557 |
0.59933 |
0.406381 |
4250.412 |
0.89401 |
0.4 |
10.37186 |
2066 |
0.034433 |
0.937938 |
0.719687 |
0.286905 |
4938.744 |
0.889005 |
0.3 |
10.90452 |
2174 |
0.036233 |
0.924925 |
0.819933 |
0.184967 |
5618.357 |
0.88076 |
0.2 |
12.12563 |
2429 |
0.040483 |
0.928929 |
0.913921 |
0.088409 |
6496.568 |
0.87154 |
0.1 |
12.70352 |
2539 |
0.042317 |
0.908909 |
0.991857 |
0.00838 |
9006.839 |
0.86322 |
0.01 |
18.86432 |
3756 |
0.0626 |
0.906907 |
0.99916 |
8.59E-04 |
13661.67 |
0.865655 |
0.001 |
25.45729 |
5066 |
0.084433 |
0.893894 |
0.999918 |
8.28E-05 |
21811.38 |
0.872898 |
1.00E-04 |
38.63819 |
7692 |
0.1282 |
0.902903 |
0.999926 |
7.49E-05 |
22495.78 |
0.874558 |
9.00E-05 |
40.0603 |
7977 |
0.13295 |
0.906907 |
0.999934 |
6.62E-05 |
23493.12 |
0.872938 |
8.00E-05 |
42.41206 |
8448 |
0.1408 |
0.905906 |
0.999942 |
5.86E-05 |
23754.33 |
0.874804 |
7.00E-05 |
43.43216 |
8670 |
0.1445 |
0.910911 |
0.999951 |
4.93E-05 |
24638.54 |
0.874382 |
6.00E-05 |
44.87437 |
8940 |
0.149 |
0.902903 |
0.999959 |
4.10E-05 |
25591.86 |
0.876173 |
5.00E-05 |
46.9598 |
9354 |
0.1559 |
0.907908 |
0.999967 |
3.31E-05 |
27544.34 |
0.876485 |
4.00E-05 |
49.32663 |
9840 |
0.164 |
0.901902 |
0.999976 |
2.44E-05 |
29500.22 |
0.877858 |
3.00E-05 |
53.20101 |
10596 |
0.1766 |
0.90991 |
0.999984 |
1.64E-05 |
32686.55 |
0.877843 |
2.00E-05 |
59.0201 |
11752 |
0.195867 |
0.90991 |
0.999992 |
8.09E-06 |
40127.56 |
0.881937 |
1.00E-05 |
72.15075 |
14386 |
0.239767 |
0.916917 |
0.999993 |
7.20E-06 |
41876.3 |
0.882174 |
9.00E-06 |
76.05025 |
15140 |
0.252333 |
0.915916 |
0.999994 |
6.38E-06 |
42827.65 |
0.882782 |
8.00E-06 |
75.92965 |
15113 |
0.251883 |
0.90991 |
0.999994 |
5.67E-06 |
45319.83 |
0.883391 |
7.00E-06 |
80.84422 |
16103 |
0.268383 |
0.920921 |
0.999995 |
4.74E-06 |
48401.74 |
0.882063 |
6.00E-06 |
86.63317 |
17247 |
0.28745 |
0.915916 |
0.999996 |
4.03E-06 |
52139.26 |
0.884145 |
5.00E-06 |
93.47236 |
18609 |
0.31015 |
0.921922 |
0.999997 |
3.26E-06 |
57559.79 |
0.884181 |
4.00E-06 |
102.2261 |
20343 |
0.33905 |
0.923924 |
0.999998 |
2.38E-06 |
68157.14 |
0.888698 |
3.00E-06 |
122.0854 |
24310 |
0.405167 |
0.922923 |
0.999998 |
1.58E-06 |
90160.77 |
0.883803 |
2.00E-06 |
162.1357 |
32267 |
0.537783 |
0.920921 |
0.999999 |
7.54E-07 |
136942.9 |
0.884135 |
1.00E-06 |
246.6382 |
49081 |
0.818017 |
0.935936 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.7 |
c |
||||||
0.3 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.499574 |
0.516069 |
181.598 |
0.299521 |
0.5 |
2.351759 |
468 |
0.0078 |
0.431431 |
0.603308 |
0.403244 |
4161.523 |
0.8816 |
0.4 |
10.51256 |
2109 |
0.03515 |
0.938939 |
0.720446 |
0.285064 |
5090.678 |
0.876962 |
0.3 |
10.66332 |
2122 |
0.035367 |
0.927928 |
0.819105 |
0.183854 |
5576.99 |
0.874825 |
0.2 |
10.99497 |
2188 |
0.036467 |
0.921922 |
0.914607 |
0.088364 |
6373.834 |
0.865982 |
0.1 |
11.83417 |
2355 |
0.03925 |
0.906907 |
0.991859 |
0.008432 |
9179.874 |
0.863959 |
0.01 |
17.33668 |
3465 |
0.05775 |
0.906907 |
0.999178 |
8.35E-04 |
13354.09 |
0.868713 |
0.001 |
24.28141 |
4832 |
0.080533 |
0.8999 |
0.999917 |
8.33E-05 |
21958.43 |
0.877858 |
1.00E-04 |
38.9799 |
7757 |
0.129283 |
0.90991 |
0.999925 |
7.56E-05 |
22522.38 |
0.878406 |
9.00E-05 |
40.44221 |
8049 |
0.13415 |
0.904905 |
0.999935 |
6.60E-05 |
23078.95 |
0.879306 |
8.00E-05 |
40.58291 |
8091 |
0.13485 |
0.90991 |
0.999943 |
5.76E-05 |
24030.42 |
0.880363 |
7.00E-05 |
42.77889 |
8514 |
0.1419 |
0.908909 |
0.999951 |
4.94E-05 |
24621.14 |
0.87991 |
6.00E-05 |
43.65327 |
8687 |
0.144783 |
0.910911 |
0.999959 |
4.11E-05 |
26012.24 |
0.88232 |
5.00E-05 |
45.75377 |
9106 |
0.151767 |
0.910911 |
0.999967 |
3.28E-05 |
27212.47 |
0.882244 |
4.00E-05 |
48.61809 |
9676 |
0.161267 |
0.91992 |
0.999975 |
2.47E-05 |
29759 |
0.884784 |
3.00E-05 |
52.51256 |
10450 |
0.174167 |
0.921922 |
0.999984 |
1.62E-05 |
32716.42 |
0.8857 |
2.00E-05 |
57.48744 |
11440 |
0.190667 |
0.915916 |
0.999992 |
8.01E-06 |
40474.56 |
0.890539 |
1.00E-05 |
69.8794 |
13906 |
0.231767 |
0.922923 |
0.999993 |
7.26E-06 |
41655.76 |
0.892093 |
9.00E-06 |
73.37688 |
14602 |
0.243367 |
0.91992 |
0.999994 |
6.35E-06 |
43837.8 |
0.892833 |
8.00E-06 |
75.29648 |
14984 |
0.249733 |
0.917918 |
0.999994 |
5.72E-06 |
45508.2 |
0.892898 |
7.00E-06 |
78.9196 |
15720 |
0.262 |
0.921922 |
0.999995 |
4.84E-06 |
48046.68 |
0.894608 |
6.00E-06 |
83.58794 |
16635 |
0.27725 |
0.92993 |
0.999996 |
4.09E-06 |
52130.5 |
0.89579 |
5.00E-06 |
92.37186 |
18382 |
0.306367 |
0.925926 |
0.999997 |
3.08E-06 |
58917.21 |
0.897878 |
4.00E-06 |
103.402 |
20577 |
0.34295 |
0.932933 |
0.999998 |
2.39E-06 |
69297.22 |
0.902184 |
3.00E-06 |
119.9246 |
23865 |
0.39775 |
0.935936 |
0.999998 |
1.58E-06 |
88388.22 |
0.905192 |
2.00E-06 |
153.0553 |
30458 |
0.507633 |
0.942943 |
0.999999 |
7.63E-07 |
134608.2 |
0.911686 |
1.00E-06 |
229.7487 |
45721 |
0.762017 |
0.948949 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.8 |
c |
||||||
0.2 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.49957 |
0.517276 |
178.6432 |
0.201734 |
0.5 |
2.276382 |
453 |
0.00755 |
0.571572 |
0.596191 |
0.409275 |
4308.121 |
0.863985 |
0.4 |
9.879397 |
1966 |
0.032767 |
0.935936 |
0.721564 |
0.284414 |
5039.603 |
0.871897 |
0.3 |
10.20101 |
2031 |
0.03385 |
0.934935 |
0.819136 |
0.18578 |
5468.508 |
0.868648 |
0.2 |
10.49246 |
2089 |
0.034817 |
0.914915 |
0.913967 |
0.088 |
6519.111 |
0.862174 |
0.1 |
12.50251 |
2488 |
0.041467 |
0.912913 |
0.991692 |
0.008503 |
9109.593 |
0.863783 |
0.01 |
16.60804 |
3321 |
0.05535 |
0.903904 |
0.999177 |
8.44E-04 |
13365.6 |
0.873124 |
0.001 |
23.06533 |
4590 |
0.0765 |
0.914915 |
0.999918 |
8.28E-05 |
21980.47 |
0.884749 |
1.00E-04 |
37.50251 |
7463 |
0.124383 |
0.920921 |
0.999926 |
7.47E-05 |
22913.42 |
0.883321 |
9.00E-05 |
39.23618 |
7808 |
0.130133 |
0.918919 |
0.999934 |
6.65E-05 |
23212.56 |
0.885262 |
8.00E-05 |
39.67839 |
7929 |
0.13215 |
0.916917 |
0.999942 |
5.91E-05 |
23828.58 |
0.88493 |
7.00E-05 |
41.80402 |
8335 |
0.138917 |
0.921922 |
0.999952 |
4.88E-05 |
24650.27 |
0.886756 |
6.00E-05 |
43.17588 |
8593 |
0.143217 |
0.916917 |
0.999959 |
4.12E-05 |
26077.28 |
0.887304 |
5.00E-05 |
45.24121 |
9005 |
0.150083 |
0.917918 |
0.999967 |
3.29E-05 |
27834.55 |
0.886736 |
4.00E-05 |
48.25126 |
9603 |
0.16005 |
0.917918 |
0.999975 |
2.49E-05 |
29445.53 |
0.889709 |
3.00E-05 |
49.30151 |
9812 |
0.163533 |
0.924925 |
0.999984 |
1.65E-05 |
33110.89 |
0.892244 |
2.00E-05 |
56.48744 |
11242 |
0.187367 |
0.930931 |
0.999992 |
8.01E-06 |
40939.64 |
0.89988 |
1.00E-05 |
69.28141 |
13787 |
0.229783 |
0.931932 |
0.999993 |
7.23E-06 |
41251.03 |
0.901535 |
9.00E-06 |
70.90955 |
14127 |
0.23545 |
0.926927 |
0.999993 |
6.56E-06 |
43254.39 |
0.902294 |
8.00E-06 |
72.59799 |
14464 |
0.241067 |
0.933934 |
0.999994 |
5.67E-06 |
45273.62 |
0.90414 |
7.00E-06 |
76.40201 |
15235 |
0.253917 |
0.931932 |
0.999995 |
4.91E-06 |
48802.05 |
0.904774 |
6.00E-06 |
82.31658 |
16381 |
0.273017 |
0.931932 |
0.999996 |
4.08E-06 |
52308.5 |
0.90825 |
5.00E-06 |
89.9598 |
17917 |
0.298617 |
0.946947 |
0.999997 |
3.22E-06 |
56429.72 |
0.909331 |
4.00E-06 |
95.1206 |
18929 |
0.315483 |
0.946947 |
0.999998 |
2.28E-06 |
69000.35 |
0.917566 |
3.00E-06 |
115.2161 |
22928 |
0.382133 |
0.952953 |
0.999998 |
1.55E-06 |
90282.26 |
0.927214 |
2.00E-06 |
151.8141 |
30227 |
0.503783 |
0.951952 |
0.999999 |
7.41E-07 |
136573 |
0.934241 |
1.00E-06 |
227.6432 |
45301 |
0.755017 |
0.961962 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
0.9 |
c |
||||||
0.1 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.49955 |
0.516249 |
182.2814 |
0.102912 |
0.5 |
2.045226 |
422 |
0.007033 |
0.608609 |
0.59648 |
0.408358 |
4231.94 |
0.855051 |
0.4 |
9.879397 |
1967 |
0.032783 |
0.937938 |
0.717152 |
0.286692 |
4963.658 |
0.864402 |
0.3 |
9.698492 |
1930 |
0.032167 |
0.928929 |
0.818898 |
0.185611 |
5492.337 |
0.860725 |
0.2 |
10.47236 |
2085 |
0.03475 |
0.918919 |
0.913352 |
0.08792 |
6436.628 |
0.856802 |
0.1 |
11.82412 |
2353 |
0.039217 |
0.91992 |
0.991814 |
0.008432 |
9097.111 |
0.865841 |
0.01 |
17.57789 |
3498 |
0.0583 |
0.923924 |
0.999183 |
8.30E-04 |
13446.7 |
0.877003 |
0.001 |
23.85427 |
4748 |
0.079133 |
0.927928 |
0.999917 |
8.34E-05 |
22125.06 |
0.886022 |
1.00E-04 |
37.55779 |
7475 |
0.124583 |
0.942943 |
0.999927 |
7.38E-05 |
22538.11 |
0.887737 |
9.00E-05 |
37.86935 |
7537 |
0.125617 |
0.93994 |
0.999934 |
6.61E-05 |
23101.24 |
0.888532 |
8.00E-05 |
39.25628 |
7812 |
0.1302 |
0.937938 |
0.999943 |
5.80E-05 |
23967.55 |
0.887994 |
7.00E-05 |
40.37186 |
8050 |
0.134167 |
0.941942 |
0.999951 |
4.97E-05 |
25325.18 |
0.889281 |
6.00E-05 |
42.64824 |
8487 |
0.14145 |
0.926927 |
0.999959 |
4.15E-05 |
26357.19 |
0.890514 |
5.00E-05 |
45.08543 |
8972 |
0.149533 |
0.948949 |
0.999967 |
3.31E-05 |
27632.76 |
0.896303 |
4.00E-05 |
46.47236 |
9248 |
0.154133 |
0.944945 |
0.999975 |
2.50E-05 |
30036.84 |
0.896992 |
3.00E-05 |
51.74874 |
10298 |
0.171633 |
0.943944 |
0.999984 |
1.61E-05 |
32758.53 |
0.903004 |
2.00E-05 |
55.60302 |
11081 |
0.184683 |
0.937938 |
0.999992 |
7.96E-06 |
40773.38 |
0.909452 |
1.00E-05 |
69.0201 |
13751 |
0.229183 |
0.955956 |
0.999993 |
7.05E-06 |
42092.54 |
0.910735 |
9.00E-06 |
71.1005 |
14149 |
0.235817 |
0.957958 |
0.999994 |
6.49E-06 |
43774.2 |
0.910327 |
8.00E-06 |
73.9196 |
14726 |
0.245433 |
0.94995 |
0.999994 |
5.67E-06 |
45774.17 |
0.91329 |
7.00E-06 |
78.1005 |
15542 |
0.259033 |
0.948949 |
0.999995 |
4.75E-06 |
48704.56 |
0.915996 |
6.00E-06 |
81.55779 |
16230 |
0.2705 |
0.953954 |
0.999996 |
4.01E-06 |
52890.92 |
0.920347 |
5.00E-06 |
88.80402 |
17689 |
0.294817 |
0.952953 |
0.999997 |
3.15E-06 |
57608.75 |
0.926902 |
4.00E-06 |
96.25126 |
19154 |
0.319233 |
0.962963 |
0.999998 |
2.40E-06 |
67016.85 |
0.93419 |
3.00E-06 |
114.1357 |
22729 |
0.378817 |
0.968969 |
0.999998 |
1.57E-06 |
90306.9 |
0.946389 |
2.00E-06 |
152.6432 |
30376 |
0.506267 |
0.980981 |
0.999999 |
7.32E-07 |
136105.9 |
0.959251 |
1.00E-06 |
227.8442 |
45342 |
0.7557 |
0.983984 |
训练集 |
0.5 |
c |
||||||
|
0.5 |
a |
||||||
测试集 |
1 |
c |
||||||
0 |
a |
|||||||
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
0.499518 |
0.516981 |
177.9095 |
6.09E-04 |
0.5 |
2.045226 |
407 |
0.006783 |
0.109109 |
0.601165 |
0.403701 |
4208.09 |
0.84492 |
0.4 |
9.824121 |
1955 |
0.032583 |
0.930931 |
0.719308 |
0.2858 |
5071.151 |
0.856746 |
0.3 |
9.809045 |
1952 |
0.032533 |
0.931932 |
0.819674 |
0.184769 |
5579.241 |
0.857264 |
0.2 |
10.64824 |
2119 |
0.035317 |
0.952953 |
0.912692 |
0.089165 |
6338.638 |
0.857128 |
0.1 |
11.61809 |
2312 |
0.038533 |
0.938939 |
0.99186 |
0.008414 |
9149.03 |
0.866193 |
0.01 |
17.22613 |
3429 |
0.05715 |
0.928929 |
0.999175 |
8.41E-04 |
13378.6 |
0.876867 |
0.001 |
23.0201 |
4582 |
0.076367 |
0.951952 |
0.999919 |
8.20E-05 |
21734.3 |
0.893491 |
1.00E-04 |
36.8392 |
7331 |
0.122183 |
0.957958 |
0.999926 |
7.48E-05 |
22469.31 |
0.896248 |
9.00E-05 |
38.23116 |
7624 |
0.127067 |
0.971972 |
0.999935 |
6.54E-05 |
23319.39 |
0.893949 |
8.00E-05 |
40.77387 |
8114 |
0.135233 |
0.948949 |
0.999942 |
5.81E-05 |
23928.25 |
0.895368 |
7.00E-05 |
40.89447 |
8139 |
0.13565 |
0.948949 |
0.999951 |
5.00E-05 |
24340.47 |
0.897646 |
6.00E-05 |
42 |
8374 |
0.139567 |
0.955956 |
0.999959 |
4.17E-05 |
25587.68 |
0.897335 |
5.00E-05 |
44.0402 |
8765 |
0.146083 |
0.955956 |
0.999967 |
3.30E-05 |
27485.81 |
0.901082 |
4.00E-05 |
47.1608 |
9401 |
0.156683 |
0.957958 |
0.999975 |
2.47E-05 |
29732.46 |
0.901761 |
3.00E-05 |
51.43216 |
10268 |
0.171133 |
0.958959 |
0.999984 |
1.60E-05 |
33218.88 |
0.909412 |
2.00E-05 |
56.33668 |
11211 |
0.18685 |
0.973974 |
0.999992 |
8.20E-06 |
40049.86 |
0.918768 |
1.00E-05 |
68.94472 |
13720 |
0.228667 |
0.960961 |
0.999993 |
7.40E-06 |
41860.41 |
0.919377 |
9.00E-06 |
71 |
14131 |
0.235517 |
0.975976 |
0.999993 |
6.53E-06 |
43537.62 |
0.922888 |
8.00E-06 |
73.67337 |
14661 |
0.24435 |
0.980981 |
0.999994 |
5.57E-06 |
45599.75 |
0.925745 |
7.00E-06 |
76.27638 |
15181 |
0.253017 |
0.972973 |
0.999995 |
4.79E-06 |
47753.81 |
0.931062 |
6.00E-06 |
79.81407 |
15900 |
0.265 |
0.983984 |
0.999996 |
4.08E-06 |
51002.03 |
0.933843 |
5.00E-06 |
87.39196 |
17391 |
0.28985 |
0.983984 |
0.999997 |
3.18E-06 |
57933.75 |
0.938179 |
4.00E-06 |
98.76884 |
19656 |
0.3276 |
0.981982 |
0.999998 |
2.34E-06 |
66033.08 |
0.95077 |
3.00E-06 |
112.191 |
22341 |
0.37235 |
0.997998 |
0.999998 |
1.59E-06 |
91024.78 |
0.965694 |
2.00E-06 |
154.3015 |
30739 |
0.512317 |
1 |
0.999999 |
7.53E-07 |
132599.5 |
0.985453 |
1.00E-06 |
221.402 |
44059 |
0.734317 |
1 |