Caret::train - 未估算的值 [英] Caret::train - Values Not Imputed

问题描述

我试图通过将knnImpute"传递给 Caret 的 train() 方法的 preProcess 参数来估算值.基于以下示例，这些值似乎没有被估算，保留为 NA，然后被忽略.我做错了什么?

I am trying to impute values by passing "knnImpute" to the preProcess argument of Caret's train() method. Based on the following example, it appears that the values are not imputed, remain as NA and are then ignored. What am I doing wrong?

非常感谢任何帮助.

library("caret")

set.seed(1234)
data(iris)

# mark 8 of the cells as NA, so they can be imputed
row <- sample (1:nrow (iris), 8)
iris [row, 1] <- NA

# split test vs training
train.index <- createDataPartition (y = iris[,5], p = 0.80, list = F)
train <- iris [ train.index, ]
test  <- iris [-train.index, ]

# train the model after imputing the missing data
fit <- train (Species ~ ., 
              train, 
              preProcess = c("knnImpute"), 
              na.action  = na.pass, 
              method     = "rpart" )
test$species.hat <- predict (fit, test)

# there is 1 obs. (of 30) in the test set equal to NA  
# this 1 obs. was not returned from predict
Error in `$<-.data.frame`(`*tmp*`, "species.hat", value = c(1L, 1L, 1L,  : 
  replacement has 29 rows, data has 30

UPDATE:我已经能够直接使用 preProcess 函数来估算值.我还是不明白为什么这在 train 函数中似乎没有发生.

UPDATE: I have been able to use the preProcess function directly to impute the values. I still don't understand why this does not seem to occur within the train function.

# attempt to impute using nearest neighbors
x <- iris [, 1:4]
pp <- preProcess (x, method = c("knnImpute"))
x.imputed <- predict (pp, newdata = x)

# expect all NAs were populated with an imputed value
stopifnot( all (!is.na (x.imputed)))
stopifnot( length (x) == length (x.imputed))

推荐答案

参见 ?predict.train:

 ## S3 method for class 'train'
 predict(object, newdata = NULL, type = "raw", na.action = na.omit, ...)

这里也有一个 na.omit:

 > length(predict (fit, test))
 [1] 29
 > length(predict (fit, test, na.action = na.pass))
 [1] 30

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