xunlian.model

SVM分类器的实现原码,SVM是一类基于统计学习理论的模式识别方法

svm_type c_svc
kernel_type rbf
gamma 0.2
nr_class 2
total_sv 34
rho 0.121558
label 1 2
nr_sv 17 17
SV
1 1:0 2:5.746 3:0.989 4:0.942 5:0.686324 
1 1:0.18 2:3.589 3:1.367 4:0.917 5:0.925882 
1 1:0.72 2:2.12 3:1.893 4:0.879 5:0.770563 
0.4160461302548678 1:0.17 2:3.675 3:1.335 4:0.931 5:0.876902 
1 1:0.11 2:2.171 3:1.895 4:0.914 5:1.02915 
1 1:0.41 2:2.697 3:1.644 4:0.893 5:0.801264 
1 1:0.7 2:1.596 3:2.194 4:0.883 5:0.817643 
1 1:0.65 2:1.546 3:2.238 4:0.87 5:1.01429 
1 1:0.29 2:2.885 3:1.67 4:0.908 5:1.0422 
1 1:0.14 2:2.343 3:1.818 4:0.919 5:0.978894 
1 1:0.09 2:2.625 3:1.695 4:0.912 5:1.23486 
1 1:0.24 2:1.89 3:2.024 4:0.917 5:0.950271 
1 1:0.43 2:1.619 3:2.143 4:0.899 5:0.710445 
1 1:0.61 2:2.121 3:1.968 4:0.878 5:0.579439 
1 1:0.59 2:2.281 3:1.89 4:0.876 5:0.863899 
1 1:0.56 2:1.505 3:2.245 4:0.885 5:0.878178 
1 1:0.82 2:1.154 3:2.475 4:0.869 5:0.811206 
-0.563911652023732 1:0.92 2:2.008 3:2.006 4:0.87 5:1.45492 
-1 1:0.69 2:1.863 3:2.033 4:0.88 5:1.38328 
-1 1:0.61 2:2.054 3:1.946 4:0.871 5:1.14049 
-0.9776125339286679 1:1.12 2:1.517 3:2.203 4:0.861 5:1.12299 
-1 1:0.74 2:2.112 3:1.916 4:0.877 5:1.29973 
-1 1:0.61 2:1.808 3:2.034 4:0.883 5:0.907177 
-1 1:0.83 2:1.748 3:2.079 4:0.871 5:0.904707 
-1 1:0.66 2:1.669 3:2.125 4:0.875 5:1.1275 
-1 1:1.23 2:1.18 3:2.464 4:0.853 5:0.834879 
-1 1:0.92 2:1.729 3:2.095 4:0.865 5:1.07573 
-1 1:0.62 2:2.555 3:1.739 4:0.888 5:1.28571 
-1 1:0.83 2:1.743 3:2.093 4:0.885 5:1.1177 
-1 1:0.02 2:3.41 3:1.429 4:0.932 5:1.32821 
-1 1:0.27 2:3.2 3:1.425 4:0.909 5:1.25196 
-0.874521944302468 1:1.43 2:1.308 3:2.366 4:0.839 5:7.25478 
-1 1:0.06 2:4.074 3:1.317 4:0.93 5:1.1237 
-1 1:0.71 2:2.066 3:1.983 4:0.875 5:1.43388