对比度只能应用于R中的系数
我试图将逻辑回归拟合到我的数据中,但我得到以下错误:对比度只能应用于R中的系数,r,R,我试图将逻辑回归拟合到我的数据中,但我得到以下错误: logistic <- lm(response ~., data = df_without, family='binomial') Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) : contrasts can be applied only to factors with 2 or more levels 我的数据帧以.Rdata文件
logistic <- lm(response ~., data = df_without, family='binomial')
Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) :
contrasts can be applied only to factors with 2 or more levels
我的数据帧以.Rdata文件的形式提供
sessionInfo()
我知道只有代码的答案会被版主追查并严加处理,但这确实说明了这一点:
# I did download the excessively large file
> table(df_without[ complete.cases(df_without), 'pymnt_plan'])
n y
0 1231 0
如果删除了缺失的观测值(如
lm
中的情况),某些变量是否可能只有一个级别?试试summary(na.omit(df_without)[sapply(df_without,is.factor)])
(未经测试)哦,你可能缺少一个g
真的吗?一个10.87 MB的文件????。。。因此logistic@BenBolker:嗯,也许不是。有三列缺少大量数据:$mths\u since\u last\u delinq$mths\u since\u record$mths\u since\u last\u major\u derog
,因此我怀疑需要集中精力理解这到底意味着什么。就风险评估而言,从未有过拖欠或“derog”(不管“derog”是什么,但听起来并不好)可能是一个有利的特征。正确的答案可能是。。。首先看看你的数据;不要等到你得到一个不好的结果。
R version 3.2.0 (2015-04-16)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.10.1 (Yosemite)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel splines stats graphics grDevices utils datasets methods base
other attached packages:
[1] Amelia_1.7.3 Rcpp_0.11.6 randomForest_4.6-10 e1071_1.6-4 plyr_1.8.2
[6] gbm_2.1.1 survival_2.38-1 glmnet_2.0-2 foreach_1.4.2 Matrix_1.2-0
[11] caret_6.0-47 ggplot2_1.0.1 lattice_0.20-31 lubridate_1.3.3 RJDBC_0.2-5
[16] rJava_0.9-6 DBI_0.3.1
loaded via a namespace (and not attached):
[1] compiler_3.2.0 nloptr_1.0.4 class_7.3-12 iterators_1.0.7 tools_3.2.0
[6] digest_0.6.8 lme4_1.1-7 memoise_0.2.1 nlme_3.1-120 gtable_0.1.2
[11] mgcv_1.8-6 brglm_0.5-9 SparseM_1.6 proto_0.3-10 BradleyTerry2_1.0-6
[16] stringr_1.0.0 gtools_3.5.0 grid_3.2.0 nnet_7.3-9 foreign_0.8-63
[21] minqa_1.2.4 reshape2_1.4.1 car_2.0-25 magrittr_1.5 scales_0.2.4
[26] codetools_0.2-11 MASS_7.3-40 pbkrtest_0.4-2 colorspace_1.2-6 quantreg_5.11
[31] stringi_0.4-1 munsell_0.4.2
# I did download the excessively large file
> table(df_without[ complete.cases(df_without), 'pymnt_plan'])
n y
0 1231 0