我遇到类似这样的问题： https://stackoverflow.com/a/4285335/190791
> fit = glm(repeater ~ bool_brand * bool_comp * bool_cat + cust_poor_rich + chain, family=binomial(logit), data=tt)#<-- submission 16
>
> pred = predict(fit, tcv, type = "response")
Error in model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) :
factor chain has new levels 525
但我找不到新级别
> id <- which(!(tcv$chain %in% levels(tt$chain)))
> id
integer(0)
以下是tt和tcv的数据结构摘录：
> str(tt)
Classes ‘data.table’ and 'data.frame': 112040 obs. of 36 variables:
$ offer : int 1198271 1198274 1208329 1208252 1199258 1199258 1208251 1203052 1203052 1200581 ...
$ id : Factor w/ 160057 levels "86246","86252",..: 53788 56484 40810 88265 28129 96116 18831 136327 121084 69563 ...
$ chain : Factor w/ 130 levels "2","3","4","6",..: 5 41 15 21 15 37 32 63 17 1 ...
etc
> str(tcv)
Classes ‘data.table’ and 'data.frame': 48017 obs. of 36 variables:
$ offer : int 1197502 1208251 1199256 1200581 1200988 1208251 1197502 1199258 1197502 1198272 ...
$ id : Factor w/ 160057 levels "86246","86252",..: 110756 15729 42581 72532 144743 7733 85601 43639 109772 138467 ...
$ chain : Factor w/ 130 levels "2","3","4","6",..: 9 44 15 68 4 50 26 15 68 73 ...
etc