Code requires these packages:
#
# Code requires these packages:
library(caret)
## Warning: package 'caret' was built under R version 4.4.3
## Loading required package: ggplot2
## Warning: package 'ggplot2' was built under R version 4.4.3
## Loading required package: lattice
library(tidymodels)
## Warning: package 'tidymodels' was built under R version 4.4.3
## ── Attaching packages ────────────────────────────────────── tidymodels 1.4.1 ──
## ✔ broom 1.0.10 ✔ rsample 1.3.1
## ✔ dials 1.4.2 ✔ tailor 0.1.0
## ✔ dplyr 1.1.4 ✔ tidyr 1.3.1
## ✔ infer 1.0.9 ✔ tune 2.0.0
## ✔ modeldata 1.5.1 ✔ workflows 1.3.0
## ✔ parsnip 1.3.3 ✔ workflowsets 1.1.1
## ✔ purrr 1.1.0 ✔ yardstick 1.3.2
## ✔ recipes 1.3.1
## Warning: package 'dials' was built under R version 4.4.3
## Warning: package 'scales' was built under R version 4.4.3
## Warning: package 'dplyr' was built under R version 4.4.2
## Warning: package 'infer' was built under R version 4.4.3
## Warning: package 'modeldata' was built under R version 4.4.3
## Warning: package 'parsnip' was built under R version 4.4.3
## Warning: package 'purrr' was built under R version 4.4.3
## Warning: package 'recipes' was built under R version 4.4.3
## Warning: package 'rsample' was built under R version 4.4.3
## Warning: package 'tailor' was built under R version 4.4.3
## Warning: package 'tidyr' was built under R version 4.4.2
## Warning: package 'tune' was built under R version 4.4.3
## Warning: package 'workflows' was built under R version 4.4.3
## Warning: package 'workflowsets' was built under R version 4.4.3
## Warning: package 'yardstick' was built under R version 4.4.3
## ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
## ✖ rsample::calibration() masks caret::calibration()
## ✖ purrr::discard() masks scales::discard()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ✖ purrr::lift() masks caret::lift()
## ✖ yardstick::precision() masks caret::precision()
## ✖ yardstick::recall() masks caret::recall()
## ✖ yardstick::sensitivity() masks caret::sensitivity()
## ✖ yardstick::specificity() masks caret::specificity()
## ✖ recipes::step() masks stats::step()
theme_set(theme_bw() + theme(legend.position = "top"))
data("segmentationData")
segmentationData$Cell <- NULL
segmentationData <- segmentationData[, c("EqSphereAreaCh1", "PerimCh1", "Class", "Case")]
names(segmentationData)[1:2] <- paste0("Predictor", LETTERS[1:2])
example_train <- subset(segmentationData, Case == "Train")
example_test <- subset(segmentationData, Case == "Test")
example_train$Case <- NULL
example_test$Case <- NULL
simple_trans_rec <- recipe(Class ~ ., data = example_train) %>%
step_BoxCox(PredictorA, PredictorB) %>%
prep(training = example_train)
simple_trans_test <- bake(simple_trans_rec, example_test)
pred_b_lambda <-
tidy(simple_trans_rec, number = 1) %>%
filter(terms == "PredictorB") %>%
select(value)
bc_before <- ggplot(example_test, aes(x = PredictorB)) +
geom_histogram(bins = 35, col = "blue", fill = "blue", alpha = .6) +
xlab("Predictor B") +
ggtitle("(a)")
bc_after <- ggplot(simple_trans_test, aes(x = PredictorB)) +
geom_histogram(bins = 35, col = "red", fill = "red", alpha = .6) +
xlab("Predictor B (inverse)") +
ggtitle("(b)")
sessionInfo()
## R version 4.4.1 (2024-06-14 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 26100)
##
## Matrix products: default
##
##
## locale:
## [1] LC_COLLATE=English_Indonesia.utf8 LC_CTYPE=English_Indonesia.utf8
## [3] LC_MONETARY=English_Indonesia.utf8 LC_NUMERIC=C
## [5] LC_TIME=English_Indonesia.utf8
##
## time zone: Asia/Jakarta
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] yardstick_1.3.2 workflowsets_1.1.1 workflows_1.3.0 tune_2.0.0
## [5] tidyr_1.3.1 tailor_0.1.0 rsample_1.3.1 recipes_1.3.1
## [9] purrr_1.1.0 parsnip_1.3.3 modeldata_1.5.1 infer_1.0.9
## [13] dplyr_1.1.4 dials_1.4.2 scales_1.4.0 broom_1.0.10
## [17] tidymodels_1.4.1 caret_7.0-1 lattice_0.22-6 ggplot2_4.0.0
##
## loaded via a namespace (and not attached):
## [1] tidyselect_1.2.1 timeDate_4041.110 farver_2.1.2
## [4] S7_0.2.0 fastmap_1.2.0 pROC_1.19.0.1
## [7] digest_0.6.37 rpart_4.1.23 timechange_0.3.0
## [10] lifecycle_1.0.4 survival_3.6-4 magrittr_2.0.3
## [13] compiler_4.4.1 rlang_1.1.6 sass_0.4.9
## [16] tools_4.4.1 yaml_2.3.10 data.table_1.16.2
## [19] knitr_1.49 plyr_1.8.9 DiceDesign_1.10
## [22] RColorBrewer_1.1-3 withr_3.0.2 nnet_7.3-19
## [25] grid_4.4.1 stats4_4.4.1 future_1.67.0
## [28] globals_0.18.0 iterators_1.0.14 MASS_7.3-60.2
## [31] cli_3.6.5 rmarkdown_2.29 generics_0.1.3
## [34] rstudioapi_0.17.1 future.apply_1.20.0 reshape2_1.4.4
## [37] cachem_1.1.0 stringr_1.5.1 splines_4.4.1
## [40] parallel_4.4.1 vctrs_0.6.5 hardhat_1.4.2
## [43] Matrix_1.7-0 jsonlite_1.8.9 listenv_0.9.1
## [46] foreach_1.5.2 gower_1.0.2 jquerylib_0.1.4
## [49] glue_1.8.0 parallelly_1.45.1 codetools_0.2-20
## [52] lubridate_1.9.4 stringi_1.8.4 gtable_0.3.6
## [55] GPfit_1.0-9 tibble_3.3.0 pillar_1.11.0
## [58] furrr_0.3.1 htmltools_0.5.8.1 ipred_0.9-15
## [61] lava_1.8.1 R6_2.5.1 lhs_1.2.0
## [64] evaluate_1.0.1 backports_1.5.0 bslib_0.8.0
## [67] class_7.3-22 Rcpp_1.0.13-1 nlme_3.1-164
## [70] prodlim_2025.04.28 xfun_0.49 ModelMetrics_1.2.2.2
## [73] pkgconfig_2.0.3