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 1 0 0 0 0 0 0 0 0 0.98998 1 0 0 0 0 0 0 0 0.99416 0.97783 1 0 0 0 0 0 0 0.99605 0.99598 0.98546 1 0 0 0 0 0 0.93951 0.89424 0.9441 0.91815 1 0 0 0 0 0.97927 0.96827 0.98872 0.96641 0.93203 1 0 0 0 0.9921 0.98708 0.99399 0.98698 0.91146 0.98665 1 0 0 0.97742 0.9875 0.97542 0.97804 0.8598 0.97399 0.9914 1 0 0.94603 0.97709 0.9174 0.96506 0.79842 0.89886 0.94248 0.96228 1
白葡萄酒的模糊相似矩阵R：
1 0 0 0 0 0 0 0.95268 1
0 0 0 0 0 0.95819 0.94967 1 0 0 0 0 0.93803 0.99065 0.95812 1 0 0 0 0.91881 0.97436 0.96537 0.9933 1 0 0 0.9802 0.95577 0.98489 0.96271 0.96377 1
0 0.98086 0.97135 0.94166 0.97025 0.95084 0.97693 1 0.98599 0.9134 0.95678 0.89722 0.88268 0.9671 0.94357 0.96269 0.96604 0.98666 0.95995 0.95172 0.96462 0.94171 0.9633 0.97844 0.97757 0.97678 0.96997 0.9696 0.96078 0.97818 0.94669 0.94665 0.93962 0.92378 0.97588 0.97532 0.99052 0.93656 0.91603 0.90628 0.87619 0.95069 0.96764 0.99381 0.94099 0.93676 0.92028 0.89972 0.97152 0.97535 0.93895 0.98525 0.91155 0.98336 0.96298 0.94292 0.98198 0.95586 0.84288 0.88842 0.83979 0.82948 0.94294 0.93303 0.94585 0.86398 0.92019 0.83857 0.83917 0.93106 0.88598 0.93816
0.9608 0.97238 0.95803 0.949 0.94871 0.92783 0.97 0.94871 0.90666 0.9328 0.90816 0.95557 0.98122 0.94477 0.90941 0.97105 0.89102 0.89328 0.94432 0.88721 0.97192 0.96702 0.9882 0.96631 0.95737 0.9779 0.95918 0.92785 0.98582 0.95356 0.99002 0.98031 0.94992 0.95359 0.9389 0.96816 0.97992 0.95808 0.95756 0.95377 0.9204 0.95623 0.98548 0.95987 0.98245 0.97035 0.96882 0.97102 0.98931 0.97658 0.97324 0.9624 0.94736 0.97765 0.97398 0.94287 0.94148 0.95909 0.94272 0.94218 0.95033 0.93257 0.95532 0.99866 0.96277 0.99127 0.97884 0.96298 0.96817 0.97417 0.9736 0.98796 0.9731 0.96667 0.98009 0.96481 0.93384 0.98909
0.96027
0.99515
0.9879
0.95845
0.96012
续上右侧
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
0
0 0
0
0
31
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
0 0.95684 1 0.93198 0.98533 0.97415 0.94093 0.97457 0.93086 0.98179 0.93726 0.88103 0.92097 0.95117 0.85901 0.94693 0.90612 0.94121 0.98644 0.94508 0.90717 0.96231 0.97215 0.96885 0.99418 0.90256 0.96241 0.93385 0.98834 0.93772 0.96423 0.96746 0.98451 0.90629 0.95942 0.92315 0.97579 0.95379 0.99248 0.90504
0.96516
0 0 0 0 0
0
0 0 0 0 0 0 1 0.92714 0.9308 0.93701 0 0 0 0 0 0 0 1
0.97044 0.98427 0 0 0 0 0 0 0 0 1 0.99537 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.95318 0.93817 0.9271 0.93255 0.86822 0.94089 0.94877 0.9636 0.91206 0.89223 0.93591 0.94358 0.95568 0.94827 0.90778 0.91866 0.91277 0.98697 0.97708 0.98428 0.94673 0.91388 0.91896 0.92881 0.97651 0.96727 0.94163 0.95254 0.95763 0.94839 0.90044 0.91416 0.9732 0.92946 0.90993 0.92139 0.95674 0.97793 0.93854 0.952 0.98983 0.95832 0.97211 0.97424 0.9885 0.88155 0.90436 0.91054 0.98248 0.95067 0.93511 0.94219 0.99699 0.94497 0.94118 0.94957 0.96666 0.9486 0.90433 0.91917 续上右侧
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 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 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0.96007 1 0 0 0.89541 0.97258 1 0 0.9726 0.9797 0.96655 1 0.91464
0.9793
0.9928
0.96705
1 0 0.85486 1
0.82747 0.92865 0.9142 0.82476 0.95834 0.93532 0.84431 0.86663 0.93225 0.88636 0.96601 0.81544 0.91535 0.82317 0.96836 0.86754 0.95189 0.91054 0.91805 0.86398 0.9774 0.84617 0.94533 0.8892 0.97181 0.82702
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 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 0 0 0 0 1 0
0
32
0 0 0 0 1 0 0.84956 1
0.8789 0.90829 0.9575 0.94646 0.89678 0.99087 0.81436 0.97954 0.89949 0.98293 0.85627 0.97809 0.94098 0.9573 0.92581 0.90696 0.87344 0.97169 0.92086 0.96777 0.82874
0.97596
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 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
0 0 0 0 1 0.8717 0.93357 0.93199 0.89859 0.96528 0.94852 0.86872 0.9449 0.92266 0.93399 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0.96033 0.98167 0.95049 0.97021 0.96488 1
0 0 0 0.93405 0.94234 0.9058 0.94162 0.90592 0.97212 1
0 0 0.92552 0.97629 0.98913 0.97903 0.98871 0.97981 0.94591 1 0 0.95941 0.98856 0.95993 0.97686 0.96368 0.99284 0.98166 0.98 1 0.90053
0.9739
0.99889
0.96871
0.99211
0.95722
0.92109
0.99219
0.9674
附录5：
多元线性回归代码二元一次线性回归
x=A(:,1); 六元一次线性回归 y=A(:,2);
x1=A(:,1); [b,bint,r,rint,stats] = regress(y,x) x2=A(:,2); clear x3=A(:,3); x4=A(:,4); x5=A(:,5);
y=A(:,6);
三元一次线性回归 [b,bint,r,rint,stats] x1=A(:,1); regress(y,[x1,x2,x3,x4,x5]) x2=A(:,2); clear y=A(:,3);
[b,bint,r,rint,stats] =
regress(y,[x1,x2]) 七元一次线性回归 clear x1=A(:,1); x2=A(:,2);
x3=A(:,3); 四元一次线性回归 x4=A(:,4); x1=A(:,1); x5=A(:,5); x2=A(:,2); x6=A(:,6); x3=A(:,3); y=A(:,7);
y=A(:,4);
[b,bint,r,rint,stats] [b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6]) regress(y,[x1,x2,x3]) clear clear
八元一次线性回归 五元一次线性回归 x1=A(:,1); x1=A(:,1); x2=A(:,2); x2=A(:,2); x3=A(:,3); x3=A(:,3); x4=A(:,4); x4=A(:,4); x5=A(:,5); y=A(:,5);
x6=A(:,6); [b,bint,r,rint,stats] = x7=A(:,7); regress(y,[x1,x2,x3,x4]) y=A(:,8);
clear [b,bint,r,rint,stats]
regress(y,[x1,x2,x3,x4,x5,x6,x7])
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0 0 0 0 1
= = =
clear
九元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8); y=A(:,9);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8]) clear
十元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8); x9=A(:,9); y=A(:,10);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8,x9]) clear
十一元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8);
34
x9=A(:,9); x10=A(:,10); y=A(:,11);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8,x9,x10]) clear
十二元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8); x9=A(:,9); x10=A(:,10); x11=A(:,11); y=A(:,12);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11]) clear
十三元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8); x9=A(:,9); x10=A(:,10); x11=A(:,11); x12=A(:,12); y=A(:,13);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8,x
9,x10,x11,x12]) clear
十四元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8); x9=A(:,9); x10=A(:,10); x11=A(:,11); x12=A(:,12); x13=A(:,13); y=A(:,14);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13]) clear
十五元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8); x9=A(:,9); x10=A(:,10); x11=A(:,11); x12=A(:,12); x13=A(:,13); x14=A(:,14); y=A(:,15);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14])
35
clear
十六元一次线性回归 x1=A(:,1); x2=A(:,2); x3=A(:,3); x4=A(:,4); x5=A(:,5); x6=A(:,6); x7=A(:,7); x8=A(:,8); x9=A(:,9); x10=A(:,10); x11=A(:,11); x12=A(:,12); x13=A(:,13); x14=A(:,14); x15=A(:,15); y=A(:,16);
[b,bint,r,rint,stats] = regress(y,[x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15]) clear