数据集必须包含R中SVM中的所有因子吗
我试图用R中的支持向量机找到新输入向量的类概率。 训练模型不会显示错误数据集必须包含R中SVM中的所有因子吗,r,svm,R,Svm,我试图用R中的支持向量机找到新输入向量的类概率。 训练模型不会显示错误 fit <-svm(device~.,data=dataframetrain, kernel="polynomial",probability=TRUE) dataframetest看起来像: > str(dataframetrain) 'data.frame': 24577 obs. of 5 variables: $ device : Factor w/ 3 levels "mob","
fit <-svm(device~.,data=dataframetrain,
kernel="polynomial",probability=TRUE)
dataframetest看起来像:
> str(dataframetrain)
'data.frame': 24577 obs. of 5 variables:
$ device : Factor w/ 3 levels "mob","pc","tab": 1 1 1 1 1 1 1 1 1 1 ...
$ geslacht : Factor w/ 2 levels "M","V": 1 1 1 1 1 1 1 1 1 1 ...
$ leeftijd : num 77 67 67 66 64 64 63 61 61 58 ...
$ invultijd: num 12 12 12 12 12 12 12 12 12 12 ...
$ type : Factor w/ 8 levels "A","B","C","D",..: 5 5 5 5 5 5 5 5 5 5 ...
> str(dataframetest)
'data.frame': 8 obs. of 4 variables:
$ geslacht : Factor w/ 1 level "M": 1 1 1 1 1 1 1 1
$ leeftijd : num 20 60 30 25 36 52 145 25
$ invultijd: num 6 12 2 5 6 8 69 7
$ type : Factor w/ 8 levels "A","B","C","D",..: 1 2 3 4 5 6 7 8
我用2个“geslacht”因子训练模型,但有时我只能用1个“geslacht”因子预测数据。
是否有可能用一个只有1个“geslacht”因子的测试集来预测类别概率
我希望有人能帮助我 将另一个级别(但不是数据)添加到geslacht
x <- factor(c("A", "A"), levels = c("A", "B"))
x
[1] A A
Levels: A B
x将另一个级别(但不是数据)添加到geslacht
x <- factor(c("A", "A"), levels = c("A", "B"))
x
[1] A A
Levels: A B
x
x <- factor(c("A", "A"))
levels(x) <- c("A", "B")
x
[1] A A
Levels: A B