SVC、scikit-learn 中的详细日志缩写含义

Question

我正在寻找 scikit-learn 中 SVC 函数的详细日志缩写的含义？

如果nSV是支持向量个数，#iter是迭代次数，nBSV,rho,obj是什么意思？

这是一个例子：

import numpy as np
from sklearn.svm import SVR
sets=np.loadtxt('data\Exp Rot.txt')         # reading data
model=SVR(kernel='rbf',C=100,gamma=1,max_iter=100000,verbose=True)
model.fit(sets[:,:2],sets[:,2])
print(model.score)

这是结果

Answer 1

scikit-learn 由同一作者使用 libsvm's implementation of support-vector machines (LinearSVC will use liblinear）。官方网站有自己的常见问题解答here。

摘录：

Q: The output of training C-SVM is like the following. What do they mean?

optimization finished, #iter = 219

nu = 0.431030

obj = -100.877286, rho = 0.424632

nSV = 132, nBSV = 107

Total nSV = 132

obj is the optimal objective value of the dual SVM problem

rho is the bias term in the decision function sgn(w^Tx - rho)

nSV and nBSV are number of support vectors and bounded support vectors (i.e., alpha_i = C)

nu-svm is a somewhat equivalent form of C-SVM where C is replaced by nu

nu simply shows the corresponding parameter. More details are in libsvm document

Link to the libsvm document mentioned above (PDF!)

SVC、scikit-learn 中的详细日志缩写含义

Verbose log abbriviations meaning in SVC, scikit-learn

python

svm

verbose

scikit-learn