[我正在尝试从一篇论文中重建一个随机森林模型，并且代码似乎没有用，我只是在学习R，这在我头上是很多事情，但是我将尽我所能进行解释。] >
论文的源代码可以在这里找到：[[[https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0181347.s002&type=supplementary)]
本文提供了两个数据集：训练和测试，然后为每个数据集创建两个子集（有关数据的head（），请参见文本底部。Data can be found in supplementary paper here
（应该能够直接复制到.csv）代码如下：
sink("test.txt", split=TRUE) print("#data process") data_bin_train<-read.csv("training.csv", head=TRUE) names(data_bin_train) data_bin_test<-read.csv("test.csv", head=TRUE) names(data_bin_test) dspt_bin_train<-subset(data_bin_train,select=c(-Deamidation)) dspt_bin_test<-subset(data_bin_test,select=c(-Deamidation)) class_bin_train<-subset(data_bin_train, select=c(Deamidation)) class_bin_test<-subset(data_bin_test, select=c(Deamidation)) library("caret") library("ROCR") library("pROC") fitControl <- trainControl(method = "CV",number = 10,returnResamp = "all", verboseIter = FALSE, classProbs = TRUE) set.seed(2)此位工作正常。然后下一点代码是我得到错误的地方：
library("randomForest") print("#Random Forest binary class via caret (randomForest)") caret_rf_bin_randomf_cv10 <- train(Deamidation~., data=data_bin_train, method = "rf", preProcess = c("center", "scale"), tuneLength = 10, trControl = fitControl) caret_rf_bin_randomf_cv10 varImp(caret_rf_bin_randomf_cv10) rf_bin_Preds <- extractPrediction(list(caret_rf_bin_randomf_cv10),testX=dspt_bin_test[,1:13], testY=class_bin_test[,1])
[.data.frame中的错误（newdata，，object $ method $ center，drop = FALSE）：未定义的列已选择`任何帮助都将是惊人的！本文使用R v 3.1.1 caret_6.0-35，而我正在运行两者的更新版本，我相信这是错误的来源，但我不确定如何解决它，或者说实话错误甚至是。
谢谢
TinoMass
下面是两个数据集的sessionInfo（）和Head（）
R version 3.5.3 (2019-03-11) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 18362) Matrix products: default attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] randomForest_4.6-14 pROC_1.15.3 ROCR_1.0-7 gplots_3.0.1.1 caret_6.0-84 [6] ggplot2_3.2.1 lattice_0.20-38 loaded via a namespace (and not attached): [1] Rcpp_1.0.3 pillar_1.4.3 compiler_3.5.3 gower_0.2.1 plyr_1.8.5 bitops_1.0-6 [7] iterators_1.0.12 class_7.3-15 tools_3.5.3 rpart_4.1-13 ipred_0.9-9 lubridate_1.7.4 [13] lifecycle_0.1.0 tibble_2.1.3 nlme_3.1-137 gtable_0.3.0 pkgconfig_2.0.3 rlang_0.4.2 [19] Matrix_1.2-15 foreach_1.4.7 rstudioapi_0.10 prodlim_2019.11.13 e1071_1.7-3 withr_2.1.2 [25] stringr_1.4.0 dplyr_0.8.3 caTools_1.17.1.3 gtools_3.8.1 generics_0.0.2 recipes_0.1.8 [31] stats4_3.5.3 grid_3.5.3 nnet_7.3-12 tidyselect_0.2.5 data.table_1.12.8 glue_1.3.1 [37] R6_2.4.1 survival_2.43-3 gdata_2.18.0 lava_1.6.6 reshape2_1.4.3 purrr_0.3.3 [43] magrittr_1.5 ModelMetrics_1.2.2 scales_1.1.0 codetools_0.2-16 MASS_7.3-51.1 splines_3.5.3 [49] assertthat_0.2.1 timeDate_3043.102 colorspace_1.4-1 KernSmooth_2.23-15 stringi_1.4.3 lazyeval_0.2.2 [55] munsell_0.5.0 crayon_1.3.4training.txt
PDB `Residue #` `AA following A… attack_distance Half_life norm_B_factor_C norm_B_factor_CA norm_B_factor_CB norm_B_factor_CG <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 11BG 67 GLY 3.84 1.02 1.46 1.46 1.36 1.38 2 11BG 17 SER 4.81 11.8 0.692 0.706 1.18 1.62 3 11BG 71 CYS 4.11 55.5 0.174 0.481 0.574 0.782 4 11BG 44 THR 3.33 49.9 -1.24 -1.30 -1.35 -1.52 5 11BG 94 CYS 4.97 60 1.41 1.64 1.92 2.15 6 11BG 27 LEU 4.52 119 -0.898 -0.905 -0.820 -0.604test.txt
PDB `Residue #` `AA following A… attack_distance Half_life norm_B_factor_C norm_B_factor_CA norm_B_factor_CB norm_B_factor_CG
<chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 1ACC 713 GLY 3.69 1.45 3.17 3.35 3.63 4.06
2 1ACC 719 GLY 4.64 1.04 0.688 0.865 1.42 1.83
3 1ACC 28 PHE 4.81 72.4 1.03 1.06 1.58 1.95
4 1ACC 52 ILE 4.73 279 0.944 1.13 1.29 1.46
5 1ACC 85 HIS 3.60 9.7 0.780 0.800 1.16 1.57
6 1ACC 104 LYS 4.51 55.5 2.22 2.47 2.69 2.91
我正在尝试从一篇论文中重建一个随机森林模型，并且该代码似乎无法正常工作，我只是在学习R，这在我头上是非常困难的，但是我将尽我所能进行解释。 ...
问题出在两个功能上：