Question

我试图通过将“knnImpute”传递给Caret的train（）方法的preProcess参数来估算值。根据以下示例，似乎不会估算值，保留为NA，然后忽略。我做错了什么？

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。我仍然不明白为什么在列车功能中似乎没有这种情况。

# 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))

Answer 1

请参阅?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

最高

Caret :: train - 价值没有估算

1 个答案: