R:我们如何打印 SVM 的准确率百分比

Question

这是我的示例 R 代码:

    train <- read.csv("Train.csv")
    test <- read.csv("Test+.csv")

   x <- model.matrix(age ~ . - 1,data=train)           

    classify=svm(as.factor(age)~ ., data=train,method="class")
    pred = predict(classify,test,type="class")

我怎样才能打印出准确率百分比？我想显示所有性能指标，例如准确度、精确度、召回率等，以供我评估。

Answer 1

这里有几个选项，使用内置的 iris 数据框进行说明:

library(e1071)

m1 <- svm(Species ~ ., data = iris)

使用table函数创建混淆矩阵:

table(predict(m1), iris$Species, dnn=c("Prediction", "Actual"))   

            Actual
Prediction   setosa versicolor virginica
setosa         50          0         0
versicolor      0         48         2
virginica       0          2        48

使用 caret 包生成混淆矩阵和其他模型诊断(您也可以使用 caret for the entire model development, tuning and validation process ):

library(caret)

confusionMatrix(iris$Species, predict(m1))

Confusion Matrix and Statistics

            Reference
Prediction   setosa versicolor virginica
setosa         50          0         0
versicolor      0         48         2
virginica       0          2        48

Overall Statistics

Accuracy : 0.9733          
95% CI : (0.9331, 0.9927)
No Information Rate : 0.3333          
P-Value [Acc > NIR] : < 2.2e-16       

Kappa : 0.96            
Mcnemar's Test P-Value : NA              

Statistics by Class:

                     Class: setosa Class: versicolor Class: virginica
Sensitivity                 1.0000            0.9600           0.9600
Specificity                 1.0000            0.9800           0.9800
Pos Pred Value              1.0000            0.9600           0.9600
Neg Pred Value              1.0000            0.9800           0.9800
Prevalence                  0.3333            0.3333           0.3333
Detection Rate              0.3333            0.3200           0.3200
Detection Prevalence        0.3333            0.3333           0.3333
Balanced Accuracy           1.0000            0.9700           0.9700