R:使用因子变量预测线性回归模型时的误差

时间:2018-04-22 21:01:36

标签: r linear-regression

library(ggplot2)
set.seed(1)
train.ind <- sample(1:nrow(mpg), round(nrow(mpg)/2))
lm_mod <- lm(displ ~ ., data = mpg[train.ind, ])
lm_pred <- predict(lm_mod,  mpg[-train.ind, ])

运行最后一行给出了错误:

Error in model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) : 
  factor model has new levels land cruiser wagon 4wd

我很困惑,因为我在mpg数据中没有任何因子变量。

> str(mpg)
Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   234 obs. of  11 variables:
 $ manufacturer: chr  "audi" "audi" "audi" "audi" ...
 $ model       : chr  "a4" "a4" "a4" "a4" ...
 $ displ       : num  1.8 1.8 2 2 2.8 2.8 3.1 1.8 1.8 2 ...
 $ year        : int  1999 1999 2008 2008 1999 1999 2008 1999 1999 2008 ...
 $ cyl         : int  4 4 4 4 6 6 6 4 4 4 ...
 $ trans       : chr  "auto(l5)" "manual(m5)" "manual(m6)" "auto(av)" ...
 $ drv         : chr  "f" "f" "f" "f" ...
 $ cty         : int  18 21 20 21 16 18 18 18 16 20 ...
 $ hwy         : int  29 29 31 30 26 26 27 26 25 28 ...
 $ fl          : chr  "p" "p" "p" "p" ...
 $ class       : chr  "compact" "compact" "compact" "compact" ...

我该如何解决这个问题?

0 个答案:

没有答案