SVM模型中的错误:预处理方法仅限于:BoxCox,R中的YeoJohnson
我试图运行一个SVM模型,但我得到了错误: 错误:预处理方法仅限于:BoxCox、YeoJohnson、expoTrans、Invhyperpolicsine、center、scale、range、KNIMPUTE、bagImpute、medianImpute、pca、ica、spatialSign、ignore、keep、remove、zv、nzv、conditionalX、corr 我不明白出了什么问题SVM模型中的错误:预处理方法仅限于:BoxCox,R中的YeoJohnson,r,machine-learning,nlp,svm,r-caret,R,Machine Learning,Nlp,Svm,R Caret,我试图运行一个SVM模型,但我得到了错误: 错误:预处理方法仅限于:BoxCox、YeoJohnson、expoTrans、Invhyperpolicsine、center、scale、range、KNIMPUTE、bagImpute、medianImpute、pca、ica、spatialSign、ignore、keep、remove、zv、nzv、conditionalX、corr 我不明白出了什么问题 svm.model_unigrams = train(outcome ~.
svm.model_unigrams = train(outcome ~.
, data = training_set_unigrams
, trControl = training_controls
, method = "svmRadial"
, preProcess = (training_set_unigrams, method = c("center", "scale"))
, na.action = na.pass)
由于您没有提供任何数据,因此,我使用IRIS数据
library(caret)
data(iris)
svm.model_unigrams = train(Species ~., data = iris,
trControl = trainControl(method = "cv",
number = 5,
allowParallel = TRUE),
method = "svmRadial",
preProc = c("center", "scale"),
na.action = na.pass)
类似地,您可以使用其他方法,如
train(Species ~., data = iris,
trControl = trainControl(method = "cv",
number = 5,
allowParallel = TRUE),
method = "svmRadial",
preProc = c("BoxCox"),
na.action = na.pass)
由于您没有提供任何数据,因此,我使用IRIS数据
library(caret)
data(iris)
svm.model_unigrams = train(Species ~., data = iris,
trControl = trainControl(method = "cv",
number = 5,
allowParallel = TRUE),
method = "svmRadial",
preProc = c("center", "scale"),
na.action = na.pass)
类似地,您可以使用其他方法,如
train(Species ~., data = iris,
trControl = trainControl(method = "cv",
number = 5,
allowParallel = TRUE),
method = "svmRadial",
preProc = c("BoxCox"),
na.action = na.pass)
我得到了错误:继承中的错误(x,“矩阵”):参数“x”丢失,没有默认替换
预处理(训练集
带有preProc=c(“中心”,“缩放”)
我得到了错误:继承中的错误(x,“矩阵”):参数“x”丢失,没有默认替换预处理(训练集单图,方法=c(“中心”、“比例”)
与prepoc=c(“中心”、“比例”)