我正在使用python的libsvm(svmutils)作爲分類任務。分類器是確切的。然而,我得到這樣的輸出:在libsvm中禁止輸出(python)
*
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)
有沒有什麼辦法可以壓制這個對話框?分類器服務非常好,我只是好奇。另外,"Accuracy"
代表什麼?爲什麼在我的情況下這是0%? (該數據是在80分的尺寸不相重疊的共計4類我也歸正確。。。)
其實,我有一些訓練數據屬於4每個類都有80個維度的特徵向量,4個單獨分類器用於測試單個測試點。在這種情況下,它是否通過如下方式計算精度:「如果測試點已在訓練過程中標記過,則交叉驗證成功並且準確性爲100%,否則交叉驗證失敗且準確性爲0」(它將僅爲0或100 %,因爲測試數據只有一個點)?我是否正確?謝謝,答案有所幫助。 –