我使用Python的LIbSVM(SvMuTILS)进行分类任务。分类器是精确的。但是,我得到的输出如下:

*
optimization finished, #iter = 75
nu = 0.000021
obj = -0.024330, rho = 0.563710
nSV = 26, nBSV = 0
Total nSV = 26
*
optimization finished, #iter = 66
nu = 0.000030
obj = -0.035536, rho = -0.500676
nSV = 21, nBSV = 0
Total nSV = 21
*
optimization finished, #iter = 78
nu = 0.000029
obj = -0.033921, rho = -0.543311
nSV = 23, nBSV = 0
Total nSV = 23
*
optimization finished, #iter = 90
nu = 0.000030
obj = -0.035333, rho = -0.634721
nSV = 23, nBSV = 0
Total nSV = 23
Accuracy = 0% (0/1) (classification)
Accuracy = 0% (0/1) (classification)
Accuracy = 0% (0/1) (classification)
Accuracy = 0% (0/1) (classification)

有什么方法可以抑制这个对话框吗?分类器服务得很好,我只是好奇。还有,"Accuracy"代表什么?为什么在我的情况下是0%?(数据在80个维度上不重叠。总共4节课。我也把它规范化了。

最佳答案

使用-q参数选项

import svmutil
param = svmutil.svm_parameter('-q')
...


import svmutil
x = [[0.2, 0.1], [0.7, 0.6]]
y = [0, 1]
svmutil.svm_train(y, x, '-q')

08-25 05:22