错误:在Caret中使用Train时,nrow(x)== n不为TRUE

Question

我有一个看起来像的训练集

Name       Day         Area         X    Y    Month Night
ATTACK    Monday   LA           -122.41 37.78   8      0
VEHICLE  Saturday  CHICAGO      -1.67    3.15   2      0
MOUSE     Monday   TAIPEI       -12.5    3.1    9      1

Name是结果/因变量.我转换Name,Area并Day为因素,但我不知道我是否应该为Month和Night,只取整数值1-12和0-1分别.

然后我将数据转换为矩阵

ynn <- model.matrix(~Name , data = trainDF)
mnn <- model.matrix(~ Day+Area +X + Y + Month + Night, data = trainDF)

然后我设置调整参数

nnTrControl=trainControl(method = "repeatedcv",number = 3,repeats=5,verboseIter = TRUE, returnData = FALSE, returnResamp = "all", classProbs = TRUE, summaryFunction = multiClassSummary,allowParallel = TRUE)
nnGrid = expand.grid(.size=c(1,4,7),.decay=c(0,0.001,0.1))
model <- train(y=ynn, x=mnn, method='nnet',linout=TRUE, trace = FALSE, trControl = nnTrControl,metric="logLoss", tuneGrid=nnGrid)

不过,我得到了错误Error: nrow(x) == n is not TRUE的model<-train

如果我使用xgboost而不是,我也会得到类似的错误nnet

有谁知道这导致了什么？

Answer 1

y应该是包含每个样本结果的数字或因子向量,而不是矩阵.运用

train(y = make.names(trainDF$Name), ...)

帮助,make.names修改值,使它们可以是有效的变量名称.