R 从数据帧创建混淆矩阵

我有一个名为

conf_mat

的数据框，它有两列，包括每个对象中的预测值和参考值。我在这个数据框中有20个对象

 dput(Conf_mat)
structure(list(Predicted = c(100, 200, 200, 100, 100, 200, 200, 
200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200
), Reference = c(600, 200, 200, 200, 200, 200, 200, 200, 500, 
500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200)), .Names = c("Predicted", 
"Reference"), row.names = c(NA, 20L), class = "data.frame")

我想用这种结构从这个表中创建一个混淆矩阵，它将由

Conf\u mat

dataframe填充。这将允许我计算分类的准确度评估。谢谢你的帮助

    100 200 300 400 500 600
100  NA  NA  NA  NA  NA  NA
200  NA  NA  NA  NA  NA  NA
300  NA  NA  NA  NA  NA  NA
400  NA  NA  NA  NA  NA  NA
500  NA  NA  NA  NA  NA  NA
600  NA  NA  NA  NA  NA  NA

1）尝试以下操作：

table(Conf_mat)

2）如果要强制显示级别100、200、…、600：

conf_mat_tab <- table(lapply(Conf_mat, factor, levels = seq(100, 600, 100)))

其中：

Confusion Matrix and Statistics

         Reference
Predicted 100 200 300 400 500 600
      100   0   9   0   0   1   1
      200   0   6   0   0   1   0
      300   0   0   0   0   0   0
      400   0   0   0   0   0   0
      500   0   1   0   0   1   0
      600   0   0   0   0   0   0

Overall Statistics

               Accuracy : 0.35            
                 95% CI : (0.1539, 0.5922)
    No Information Rate : 0.8             
    P-Value [Acc > NIR] : 1               

                  Kappa : 0.078           
 Mcnemar's Test P-Value : NA              

Statistics by Class:

                     Class: 100 Class: 200 Class: 300 Class: 400 Class: 500 Class: 600
Sensitivity                  NA     0.3750         NA         NA     0.3333       0.00
Specificity                0.45     0.7500          1          1     0.9412       1.00
Pos Pred Value               NA     0.8571         NA         NA     0.5000        NaN
Neg Pred Value               NA     0.2308         NA         NA     0.8889       0.95
Prevalence                 0.00     0.8000          0          0     0.1500       0.05
Detection Rate             0.00     0.3000          0          0     0.0500       0.00
Detection Prevalence       0.55     0.3500          0          0     0.1000       0.00
Balanced Accuracy            NA     0.5625         NA         NA     0.6373       0.50

Confusion Matrix and Statistics

         Reference
Predicted 100 200 300 400 500 600
      100   0   9   0   0   1   1
      200   0   6   0   0   1   0
      300   0   0   0   0   0   0
      400   0   0   0   0   0   0
      500   0   1   0   0   1   0
      600   0   0   0   0   0   0

Overall Statistics

               Accuracy : 0.35            
                 95% CI : (0.1539, 0.5922)
    No Information Rate : 0.8             
    P-Value [Acc > NIR] : 1               

                  Kappa : 0.078           
 Mcnemar's Test P-Value : NA              

Statistics by Class:

                     Class: 100 Class: 200 Class: 300 Class: 400 Class: 500 Class: 600
Sensitivity                  NA     0.3750         NA         NA     0.3333       0.00
Specificity                0.45     0.7500          1          1     0.9412       1.00
Pos Pred Value               NA     0.8571         NA         NA     0.5000        NaN
Neg Pred Value               NA     0.2308         NA         NA     0.8889       0.95
Prevalence                 0.00     0.8000          0          0     0.1500       0.05
Detection Rate             0.00     0.3000          0          0     0.0500       0.00
Detection Prevalence       0.55     0.3500          0          0     0.1000       0.00
Balanced Accuracy            NA     0.5625         NA         NA     0.6373       0.50