Question

当我尝试在插入符号中训练一个简单的lm上的一些数据时，它会返回：

> rdati<-read.csv("cutDati.csv")
> 
> rdati[]<-lapply(rdati, factor)
> 
> dataM=as.data.frame(rdati[])
> dataM=dataM[1:100,]
> 
> data=na.omit(dataM)
> trainIndex <- createDataPartition(data$d90, p = .8,
+                                   list = FALSE,
+                                   times = 1)
Warning messages:
1: In createDataPartition(data$d90, p = 0.8, list = FALSE, times = 1) :
  Some classes have no records ( 4, 6, 7, 9, 10, 11, 14, 15, 16, 17, 20, 21, 22, 23, 25 ) and these will be ignored
2: In createDataPartition(data$d90, p = 0.8, list = FALSE, times = 1) :
  Some classes have a single record ( 1 ) and these will be selected for the sample
> training <- data[ trainIndex,]
> testing  <- data[-trainIndex,]
> 
> fit <- train(d90 ~ ., data = training,
+                  method = "svmLinear",
+                  verbose = FALSE)
Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) : 
  contrasts can be applied only to factors with 2 or more levels

d90包含因子-1到27而没有0。

有人能帮助我吗？：）

谢谢，马可

编辑：

添加一些信息

> str(training$d90)
 Factor w/ 25 levels "-1","1","2","3",..: 24 2 14 4 13 6 4 4 14 6 ...
> unique(training$d90)
 [1] 26 1  13 3  12 5  27 8  -1 2 
Levels: -1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 20 21 22 23 25 26 27

我发现如果我限制它的工作区域。

training <- data[ trainIndex,200:300]
testing  <- data[-trainIndex,200:300]

fit <- train(d90 ~ ., data = training,
                 method = "svmLinear",
                 verbose = FALSE)

我正在考虑问题在于数据，但问题可能是什么？我怎么检查？

我发现了问题，但我不明白如何解决它

我尝试了一些组合，我看到错误在第205列

> unique(training[,205])
Error in `[.data.frame`(training, , 205) : 
undefined columns selected

你能帮助我吗？

使用插入符号

0 个答案: