我正在尝试使用遗传算法或模拟退火来使用插入符号特征选择,并且在这两种情况下我都会收到相同的错误消息。
我已经用非常简单的输入数据框尝试了最基本的 gafs 和 safs 形式。
> library(caret)
> head(n)
id group hs.grad race gender age m.status political n.kids income score time1 time2 time3
1 ID.1 control no white female 37 divorced other 1 96000 0.71 99.02 101.72 100.07
2 ID.2 control yes white male 34 divorced independent 0 16000 -0.43 43.78 45.54 45.79
3 ID.3 treat yes white female 39 never democrat 2 13000 1.80 100.23 101.01 103.00
4 ID.4 control yes white female 29 married independent 4 12000 -0.05 95.64 99.61 96.38
5 ID.5 control yes white female 36 married democrat 0 7000 -0.50 47.25 47.25 49.11
6 ID.6 control yes asian male 19 never republican 0 18000 0.00 77.66 78.43 85.68
> obj <- gafs(x=n[,1:8],
+ y=n$time3,
+ iters = 10)
Error in gafs.default(x = n[, 1:8], y = n$time3, iters = 10) :
promise already under evaluation: recursive default argument reference or earlier problems?
如果有人遇到类似问题,如果有人可以分享经验,我将不胜感激(顺便说一句,n 只有 14 个观察值,尽管我尝试了许多不同的数据帧并得到相同的错误消息)
谢谢