R predict.lm函數給出錯誤大小的輸出。如何解決R predict.lm錯誤的輸出長度?
stocks = read.csv("some-file.csv", header = TRUE)
## 75% of the sample size
smp_size <- floor(0.75 * nrow(stocks))
## set the seed to make your partition reproductible
set.seed(123)
train_ind <- sample(seq_len(nrow(stocks)), size = smp_size)
train <- stocks[train_ind, ]
test <- stocks[-train_ind, ]
model = lm (train$Open ~ train$Close, data=train)
model
predicted<-predict.lm(model, test$Open)
length(test$Open)
length(predicted)
length(test$Close)
> length(test$Open)
[1] 16994
> length(predicted)
[1] 50867
> length(test$Close)
[1] 16994
爲什麼發生這種情況?預測函數的輸出長度應該等於測試$ Open的長度,對不對?
改變了它的話,但是同樣的問題繼續存在。 而且它顯示我錯誤'>預測<-predict.lm(型號,newdata =測試$打開) 錯誤的eval(predvars ,data,env): 數字'envir'arg不是長度爲' –
@VishwajeetVatharkar,你有沒有看過lm的幫助?你爲什麼繼續使用