我想使用Caret提供的一个未包含的软件包,并且遇到一个我无法弄清楚的错误,有什么想法?我用following link上手在火车上使用自己的模型(插入符号包)?
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$predict<-bmsPred
library(caret)
data.train<-data.frame(runif(100),runif(100),runif(100),runif(100),runif(100))#synthetic data for testing
bms(cbind(data.train[,1],data.train[,-1]),burn=5000,iter=100000,nmodel=1000,mcmc="bd",g="UIP",mprior.size=2)#function out of caret is working
preProcess=c('center','scale')
myTimeControl <- trainControl(method = "timeslice",initialWindow = 0.99*nrow(data.train), horizon = 1, fixedWindow = FALSE)
tune <- train(data.train[,-1],data.train[,1],preProcess=preProcess,method = bmsMeth,tuneLength=2,metric= "RMSE",trControl =myTimeControl,type="Regression")
错误我得到:
错误train.default(data.train [,-1],data.train [1],预处理= prerior::Stopping此外:警告消息:1:在 eval(expr,envir,enclos):模型适合Training1失败: mprior.size = 2方法$ fit中出错(x = x,y = y,wts = wts,param = tuneValue,lev = obsLevels,:未使用的参数(wts = wts,last = last,classProbs = classProbs,type =“Regression”)
2:在nominalTrainWorkflow中(x = x,y = y,wts =权重,info = )trainInfo,:在重采样性能 度量中存在缺失值。
为目的在寻找解决方案时,我认为要搜索的确切英文文本是“尝试应用非功能”。 – eipi10
感谢您的版本! –
你可以让你的问题在一个小例子中重现吗? –