我试图使用Caret附带的包装中未包含的火车，但收到一个我无法弄清楚的错误，知道吗？我用following link开始
bmsMeth<-list(type="Regression",library="BMS",loop=NULL,prob=NULL)
prm<-data.frame(parameter="mprior.size",class="numeric",label="mprior.size")
bmsMeth$parameters<-prm
bmsGrid<-function(x,y,len=NULL){
out<-expand.grid(mprior.size=seq(2,3,by=len))
out
}
bmsMeth$grid<-bmsGrid
bmsFit<-function(x,y,param, lev=NULL) {bms(cbind(y,x),burn=5000,iter=100000,nmodel=1000,mcmc="bd",g="UIP",mprior.size=param$mprior.size)}
bmsMeth$fit<-bmsFit
bmsPred<-function(modelFit,newdata,preProcess=NULL,submodels=NULL){predict(modelFit,newdata)}
bmsMeth$predict<-bmsPred
library(caret)
data.train<-data.frame(runif(100),runif(100),runif(100),runif(100),runif(100))#synthetic data for testing
bms(cbind(data.train[,1],data.train[,-1]),burn=5000,iter=100000,nmodel=1000,mcmc="bd",g="UIP",mprior.size=2)#function out of caret is working
preProcess=c('center','scale')
myTimeControl <- trainControl(method = "timeslice",initialWindow = 0.99*nrow(data.train), horizon = 1, fixedWindow = FALSE)
tune <- train(data.train[,-1],data.train[,1],preProcess=preProcess,method = bmsMeth,tuneLength=2,metric= "RMSE",trControl =myTimeControl,type="Regression")
错误我得到：
train.default（data.train [，-1]，data.train [，1]，preProcess =
preProcess ，：正在停止另外：警告消息：1：在
eval（expr，envir，enclos）：Training1的模型拟合失败：
mprior.size = 2方法错误$ fit（x = x，y = y，wts = wts，param =
tuneValue，lev = obsLevels，：未使用的参数（wts = wts，last =
最后，classProbs = classProbs，类型=“回归”）
2：在nominalTrainWorkflow（x = x，y = y，wts =重量，信息=
trainInfo：重采样性能中缺少值
措施。
最佳答案
显然，即使我从未使用过参数，我也只需将其放入函数中：
bmsFit<-function(x,y,param, lev=NULL, last, weights, classProbs, ...) {bms(data.frame(y,x),burn=5000,iter=100000,nmodel=1000,mcmc="bd",g="UIP",mprior.size=param$mprior.size)}