(1) preProcess not working inside train? (2) make preProcess transform response inside train.

train, preProcess Bug? Categorical variables preprocessed differently inside train vs. outside train. Bug? Does not preprocess inside train despite saying it does. Enhancement: Make preProcess transform response inside train Thanks for caret and tidy models!

library(caret)
#> Loading required package: ggplot2
#> Loading required package: lattice

df <- mtcars[c("mpg", "wt", "am")]
# Change am to factor ("0" or "1")
df$am <- factor(df$am)
df[c(1, 4), ]
#>                 mpg    wt am
#> Mazda RX4      21.0 2.620  1
#> Hornet 4 Drive 21.4 3.215  0
str(df, nchar.max = 20)
#> 'data.frame':    32 obs. of  3 variables:
#>  $ mpg: num  21 21| __truncated__ ...
#>  $ wt : num  2.62 | __truncated__ ...
#>  $ am : Factor w/ 2 levels "0","1": 2 2 2 1 1 1 1 1 1 1 ...

# preProcess only transforms predictors inside train, not response.
# Exclude response (mpg) to make preProcesses of two models similar.
preProcValues <- caret::preProcess(df[c("wt", "am")], method = c("center", "scale"))
trainTransformed <- predict(preProcValues, df)
model_formula <- formula(mpg ~ wt + am)

# transformed outside train
preproc_out <- caret::train(
  form = model_formula,
  data = trainTransformed,
  method = "lm"
)

# transformed inside train
preproc_in <- caret::train(
  form = model_formula,
  data = df,
  method = "lm",
  preProcess = c("center", "scale")
)

preProcValues # Categorical variable ignored outside train
#> Created from 32 samples and 2 variables
#> 
#> Pre-processing:
#>   - centered (1)
#>   - ignored (1)
#>   - scaled (1)
preproc_in$preProcess # Categorical variable not ignored inside train
#> Created from 32 samples and 2 variables
#> 
#> Pre-processing:
#>   - centered (2)
#>   - ignored (0)
#>   - scaled (2)
preproc_out$trainingData[c(1, 4), ] # centred and scaled outside train
#>                .outcome           wt am
#> Mazda RX4          21.0 -0.610399567  1
#> Hornet 4 Drive     21.4 -0.002299538  0
preproc_in$trainingData[c(1, 4), ] # not centred and scaled inside train, but says they were
#>                .outcome    wt am
#> Mazda RX4          21.0 2.620  1
#> Hornet 4 Drive     21.4 3.215  0

identical(preProcValues, preproc_in$preProcess)
#> [1] FALSE
identical(preproc_out$trainingData, preproc_in$trainingData)
#> [1] FALSE
identical(preproc_out$finalModel, preproc_in$finalModel)
#> [1] FALSE

^{Created on 2023-05-06 with reprex v2.0.2}

Session info

``` r sessioninfo::session_info() #> ─ Session info ─────────────────────────────────────────────────────────────── #> setting value #> version R version 4.2.3 (2023-03-15) #> os macOS Ventura 13.3.1 #> system aarch64, darwin20 #> ui X11 #> language (EN) #> collate en_US.UTF-8 #> ctype en_US.UTF-8 #> tz America/Toronto #> date 2023-05-06 #> pandoc 2.19.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown) #> #> ─ Packages ─────────────────────────────────────────────────────────────────── #> package * version date (UTC) lib source #> caret * 6.0-94 2023-03-21 [1] CRAN (R 4.2.0) #> class 7.3-22 2023-05-03 [1] CRAN (R 4.2.3) #> cli 3.6.1 2023-03-23 [1] CRAN (R 4.2.0) #> codetools 0.2-19 2023-02-01 [1] CRAN (R 4.2.3) #> colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.2.0) #> data.table 1.14.8 2023-02-17 [1] CRAN (R 4.2.0) #> digest 0.6.31 2022-12-11 [1] CRAN (R 4.2.0) #> dplyr 1.1.2 2023-04-20 [1] CRAN (R 4.2.0) #> evaluate 0.21 2023-05-05 [1] CRAN (R 4.2.0) #> fansi 1.0.4 2023-01-22 [1] CRAN (R 4.2.0) #> fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.2.0) #> foreach 1.5.2 2022-02-02 [1] CRAN (R 4.2.0) #> fs 1.6.2 2023-04-25 [1] CRAN (R 4.2.0) #> future 1.32.0 2023-03-07 [1] CRAN (R 4.2.0) #> future.apply 1.10.0 2022-11-05 [1] CRAN (R 4.2.0) #> generics 0.1.3 2022-07-05 [1] CRAN (R 4.2.0) #> ggplot2 * 3.4.2 2023-04-03 [1] CRAN (R 4.2.0) #> globals 0.16.2 2022-11-21 [1] CRAN (R 4.2.0) #> glue 1.6.2 2022-02-24 [1] CRAN (R 4.2.0) #> gower 1.0.1 2022-12-22 [1] CRAN (R 4.2.0) #> gtable 0.3.3 2023-03-21 [1] CRAN (R 4.2.0) #> hardhat 1.3.0 2023-03-30 [1] CRAN (R 4.2.3) #> htmltools 0.5.5 2023-03-23 [1] CRAN (R 4.2.0) #> ipred 0.9-14 2023-03-09 [1] CRAN (R 4.2.0) #> iterators 1.0.14 2022-02-05 [1] CRAN (R 4.2.0) #> knitr 1.42 2023-01-25 [1] CRAN (R 4.2.0) #> lattice * 0.21-8 2023-04-05 [1] CRAN (R 4.2.0) #> lava 1.7.2.1 2023-02-27 [1] CRAN (R 4.2.0) #> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.2.0) #> listenv 0.9.0 2022-12-16 [1] CRAN (R 4.2.0) #> lubridate 1.9.2 2023-02-10 [1] CRAN (R 4.2.0) #> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.0) #> MASS 7.3-60 2023-05-04 [1] CRAN (R 4.2.0) #> Matrix 1.5-4 2023-04-04 [1] CRAN (R 4.2.0) #> ModelMetrics 1.2.2.2 2020-03-17 [1] CRAN (R 4.2.0) #> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.2.0) #> nlme 3.1-162 2023-01-31 [1] CRAN (R 4.2.3) #> nnet 7.3-19 2023-05-03 [1] CRAN (R 4.2.3) #> parallelly 1.35.0 2023-03-23 [1] CRAN (R 4.2.0) #> pillar 1.9.0 2023-03-22 [1] CRAN (R 4.2.0) #> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.2.0) #> plyr 1.8.8 2022-11-11 [1] CRAN (R 4.2.0) #> pROC 1.18.0 2021-09-03 [1] CRAN (R 4.2.0) #> prodlim 2023.03.31 2023-04-02 [1] CRAN (R 4.2.0) #> purrr 1.0.1 2023-01-10 [1] CRAN (R 4.2.0) #> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.2.0) #> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.2.0) #> R.oo 1.25.0 2022-06-12 [1] CRAN (R 4.2.0) #> R.utils 2.12.2 2022-11-11 [1] CRAN (R 4.2.0) #> R6 2.5.1 2021-08-19 [1] CRAN (R 4.2.0) #> Rcpp 1.0.10 2023-01-22 [1] CRAN (R 4.2.0) #> recipes 1.0.6 2023-04-25 [1] CRAN (R 4.2.0) #> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.2.0) #> reshape2 1.4.4 2020-04-09 [1] CRAN (R 4.2.0) #> rlang 1.1.1 2023-04-28 [1] CRAN (R 4.2.0) #> rmarkdown 2.21 2023-03-26 [1] CRAN (R 4.2.3) #> rpart 4.1.19 2022-10-21 [1] CRAN (R 4.2.3) #> rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.2.0) #> scales 1.2.1 2022-08-20 [1] CRAN (R 4.2.0) #> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.0) #> stringi 1.7.12 2023-01-11 [1] CRAN (R 4.2.0) #> stringr 1.5.0 2022-12-02 [1] CRAN (R 4.2.0) #> styler 1.9.1 2023-03-04 [1] CRAN (R 4.2.0) #> survival 3.5-5 2023-03-12 [1] CRAN (R 4.2.0) #> tibble 3.2.1 2023-03-20 [1] CRAN (R 4.2.0) #> tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.2.0) #> timechange 0.2.0 2023-01-11 [1] CRAN (R 4.2.0) #> timeDate 4022.108 2023-01-07 [1] CRAN (R 4.2.0) #> utf8 1.2.3 2023-01-31 [1] CRAN (R 4.2.0) #> vctrs 0.6.2 2023-04-19 [1] CRAN (R 4.2.0) #> withr 2.5.0 2022-03-03 [1] CRAN (R 4.2.0) #> xfun 0.39 2023-04-20 [1] CRAN (R 4.2.0) #> yaml 2.3.7 2023-01-23 [1] CRAN (R 4.2.0) #> #> [1] /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/library #> #> ────────────────────────────────────────────────────────────────────────────── ```

topepo / caret

(1) preProcess not working inside train? (2) make preProcess transform response inside train. #1338