(1) preProcess not working inside train? (2) make preProcess transform response inside train.
Opened this issue · 0 comments
abanihas commented
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] FALSECreated on 2023-05-06 with reprex v2.0.2
Session info
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
#>
#> ──────────────────────────────────────────────────────────────────────────────