如何调整 tidymodels 配方参数？
How to tune a tidymodels recipe parameter?
描述
我正在尝试调整配方中的自定义参数，但我很难做到。我的印象是，这只是在配方中调用 tune("variableID") 然后将 tune_grid() 与包含列 variableID.
的网格一起使用的问题
然而，这似乎不起作用，所以我想出了一个 reprex 来说明我的方法。请注意 tune_grid() 甚至没有检测到调整参数。我在这里做错了什么？
我也尝试研究其他人是如何做的，但我在这里能找到的唯一接近我的问题的问题是 并且 tune() 的使用与预期的一样。
代表
library(tidyverse)
library(tidymodels)
#> Registered S3 method overwritten by 'tune':
#> method from
#> required_pkgs.model_spec parsnip
iris_splits <- vfold_cv(iris)
glmnet_recipe <-
recipe(formula = Species ~ Sepal.Length + Petal.Length, data = iris) %>%
step_mutate(Sepal.Length = round(Sepal.Length), digits = tune("digits")) %>%
step_zv(all_predictors()) %>%
step_normalize(all_predictors(), -all_nominal())
glmnet_spec <-
multinom_reg(penalty = 0, mixture = 0) %>%
set_mode("classification") %>%
set_engine("glmnet")
glmnet_workflow <-
workflow() %>%
add_recipe(glmnet_recipe) %>%
add_model(glmnet_spec)
glmnet_grid <- expand_grid(digits = c(0, 1))
glmnet_tune <-
tune_grid(glmnet_workflow, resamples = iris_splits, grid = glmnet_grid)
#> Warning: No tuning parameters have been detected, performance will be evaluated
#> using the resamples with no tuning. Did you want to [tune()] parameters?
#> x Fold01: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold02: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold03: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold04: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold05: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold06: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold07: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold08: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold09: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold10: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> Warning: All models failed. See the `.notes` column.
glmnet_tune$.notes[[1]]$.notes
#> [1] "preprocessor 1/1: Error: Problem with `mutate()` column `digits`.\ni `digits = tune(\"digits\")`.\nx `digits` must be a vector, not a call."
show_best(glmnet_tune)
#> Warning: No value of `metric` was given; metric 'roc_auc' will be used.
#> Error: All of the models failed. See the .notes column.
由 reprex package (v2.0.0)
于 2021-06-15 创建
会话信息
sessioninfo::session_info()
#> - Session info ---------------------------------------------------------------
#> setting value
#> version R version 4.0.5 (2021-03-31)
#> os Windows 10 x64
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate German_Germany.1252
#> ctype German_Germany.1252
#> tz Europe/Berlin
#> date 2021-06-15
#>
#> - Packages -------------------------------------------------------------------
#> package * version date lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.3)
#> backports 1.2.1 2020-12-09 [1] CRAN (R 4.0.3)
#> broom * 0.7.6 2021-04-05 [1] CRAN (R 4.0.5)
#> cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.0.3)
#> class 7.3-18 2021-01-24 [2] CRAN (R 4.0.5)
#> cli 2.5.0 2021-04-26 [1] CRAN (R 4.0.3)
#> codetools 0.2-18 2020-11-04 [2] CRAN (R 4.0.5)
#> colorspace 2.0-1 2021-05-04 [1] CRAN (R 4.0.5)
#> crayon 1.4.1 2021-02-08 [1] CRAN (R 4.0.4)
#> DBI 1.1.0 2019-12-15 [1] CRAN (R 4.0.3)
#> dbplyr 2.1.1 2021-04-06 [1] CRAN (R 4.0.5)
#> dials * 0.0.9 2020-09-16 [1] CRAN (R 4.0.4)
#> DiceDesign 1.9 2021-02-13 [1] CRAN (R 4.0.4)
#> digest 0.6.27 2020-10-24 [1] CRAN (R 4.0.3)
#> dplyr * 1.0.6 2021-05-05 [1] CRAN (R 4.0.5)
#> ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.0.3)
#> evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.3)
#> fansi 0.5.0 2021-05-25 [1] CRAN (R 4.0.5)
#> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.0.5)
#> forcats * 0.5.1 2021-01-27 [1] CRAN (R 4.0.5)
#> foreach 1.5.1 2020-10-15 [1] CRAN (R 4.0.3)
#> fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.3)
#> furrr 0.2.2 2021-01-29 [1] CRAN (R 4.0.5)
#> future 1.21.0 2020-12-10 [1] CRAN (R 4.0.3)
#> generics 0.1.0 2020-10-31 [1] CRAN (R 4.0.3)
#> ggplot2 * 3.3.3 2020-12-30 [1] CRAN (R 4.0.4)
#> glmnet * 4.1-1 2021-02-21 [1] CRAN (R 4.0.5)
#> globals 0.14.0 2020-11-22 [1] CRAN (R 4.0.3)
#> glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.3)
#> gower 0.2.2 2020-06-23 [1] CRAN (R 4.0.3)
#> GPfit 1.0-8 2019-02-08 [1] CRAN (R 4.0.4)
#> gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.3)
#> hardhat 0.1.5 2020-11-09 [1] CRAN (R 4.0.4)
#> haven 2.3.1 2020-06-01 [1] CRAN (R 4.0.3)
#> highr 0.9 2021-04-16 [1] CRAN (R 4.0.5)
#> hms 1.0.0 2021-01-13 [1] CRAN (R 4.0.5)
#> htmltools 0.5.1.9003 2021-05-07 [1] Github (rstudio/htmltools@e12171e)
#> httr 1.4.2 2020-07-20 [1] CRAN (R 4.0.5)
#> infer * 0.5.4.9000 2021-03-27 [1] Github (tidymodels/infer@66d24a0)
#> ipred 0.9-11 2021-03-12 [1] CRAN (R 4.0.4)
#> iterators 1.0.13 2020-10-15 [1] CRAN (R 4.0.3)
#> jsonlite 1.7.2 2020-12-09 [1] CRAN (R 4.0.3)
#> knitr 1.33 2021-04-24 [1] CRAN (R 4.0.5)
#> lattice 0.20-41 2020-04-02 [2] CRAN (R 4.0.5)
#> lava 1.6.9 2021-03-11 [1] CRAN (R 4.0.4)
#> lhs 1.1.1 2020-10-05 [1] CRAN (R 4.0.4)
#> lifecycle 1.0.0 2021-02-15 [1] CRAN (R 4.0.4)
#> listenv 0.8.0 2019-12-05 [1] CRAN (R 4.0.3)
#> lubridate 1.7.10 2021-02-26 [1] CRAN (R 4.0.4)
#> magrittr 2.0.1 2020-11-17 [1] CRAN (R 4.0.3)
#> MASS 7.3-53.1 2021-02-12 [2] CRAN (R 4.0.5)
#> Matrix * 1.3-2 2021-01-06 [2] CRAN (R 4.0.5)
#> modeldata * 0.1.0 2020-10-22 [1] CRAN (R 4.0.4)
#> modelr 0.1.8 2020-05-19 [1] CRAN (R 4.0.3)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.3)
#> nnet 7.3-15 2021-01-24 [2] CRAN (R 4.0.5)
#> parallelly 1.25.0 2021-04-30 [1] CRAN (R 4.0.5)
#> parsnip * 0.1.5.9003 2021-05-22 [1] Github (tidymodels/parsnip@46a2018)
#> pillar 1.6.1 2021-05-16 [1] CRAN (R 4.0.5)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.3)
#> plyr 1.8.6 2020-03-03 [1] CRAN (R 4.0.3)
#> pROC 1.17.0.1 2021-01-13 [1] CRAN (R 4.0.4)
#> prodlim 2019.11.13 2019-11-17 [1] CRAN (R 4.0.4)
#> ps 1.6.0 2021-02-28 [1] CRAN (R 4.0.5)
#> purrr * 0.3.4 2020-04-17 [1] CRAN (R 4.0.3)
#> R6 2.5.0 2020-10-28 [1] CRAN (R 4.0.3)
#> Rcpp 1.0.6 2021-01-15 [1] CRAN (R 4.0.4)
#> readr * 1.4.0 2020-10-05 [1] CRAN (R 4.0.5)
#> readxl 1.3.1 2019-03-13 [1] CRAN (R 4.0.3)
#> recipes * 0.1.16.9000 2021-05-29 [1] Github (tidymodels/recipes@0806713)
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#> tune * 0.1.5.9000 2021-05-22 [1] Github (tidymodels/tune@b0e83a7)
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配方步骤 需要有一个 tunable S3 方法用于任何你想调整的参数， 比如 digits.
查看 this article about creating your own recipe step, but I don't think you need to create your own recipe step altogether; you only need to make a tunable method for the step you are using, which is under "Other step methods"。
描述
我正在尝试调整配方中的自定义参数，但我很难做到。我的印象是，这只是在配方中调用 tune("variableID") 然后将 tune_grid() 与包含列 variableID.
然而，这似乎不起作用，所以我想出了一个 reprex 来说明我的方法。请注意 tune_grid() 甚至没有检测到调整参数。我在这里做错了什么？
我也尝试研究其他人是如何做的，但我在这里能找到的唯一接近我的问题的问题是 tune() 的使用与预期的一样。
代表
library(tidyverse)
library(tidymodels)
#> Registered S3 method overwritten by 'tune':
#> method from
#> required_pkgs.model_spec parsnip
iris_splits <- vfold_cv(iris)
glmnet_recipe <-
recipe(formula = Species ~ Sepal.Length + Petal.Length, data = iris) %>%
step_mutate(Sepal.Length = round(Sepal.Length), digits = tune("digits")) %>%
step_zv(all_predictors()) %>%
step_normalize(all_predictors(), -all_nominal())
glmnet_spec <-
multinom_reg(penalty = 0, mixture = 0) %>%
set_mode("classification") %>%
set_engine("glmnet")
glmnet_workflow <-
workflow() %>%
add_recipe(glmnet_recipe) %>%
add_model(glmnet_spec)
glmnet_grid <- expand_grid(digits = c(0, 1))
glmnet_tune <-
tune_grid(glmnet_workflow, resamples = iris_splits, grid = glmnet_grid)
#> Warning: No tuning parameters have been detected, performance will be evaluated
#> using the resamples with no tuning. Did you want to [tune()] parameters?
#> x Fold01: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold02: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold03: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold04: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold05: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold06: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold07: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold08: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold09: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> x Fold10: preprocessor 1/1: Error: Problem with `mutate()` column `digits`.
#> i `dig...
#> Warning: All models failed. See the `.notes` column.
glmnet_tune$.notes[[1]]$.notes
#> [1] "preprocessor 1/1: Error: Problem with `mutate()` column `digits`.\ni `digits = tune(\"digits\")`.\nx `digits` must be a vector, not a call."
show_best(glmnet_tune)
#> Warning: No value of `metric` was given; metric 'roc_auc' will be used.
#> Error: All of the models failed. See the .notes column.
由 reprex package (v2.0.0)
于 2021-06-15 创建 会话信息sessioninfo::session_info()
#> - Session info ---------------------------------------------------------------
#> setting value
#> version R version 4.0.5 (2021-03-31)
#> os Windows 10 x64
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate German_Germany.1252
#> ctype German_Germany.1252
#> tz Europe/Berlin
#> date 2021-06-15
#>
#> - Packages -------------------------------------------------------------------
#> package * version date lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.3)
#> backports 1.2.1 2020-12-09 [1] CRAN (R 4.0.3)
#> broom * 0.7.6 2021-04-05 [1] CRAN (R 4.0.5)
#> cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.0.3)
#> class 7.3-18 2021-01-24 [2] CRAN (R 4.0.5)
#> cli 2.5.0 2021-04-26 [1] CRAN (R 4.0.3)
#> codetools 0.2-18 2020-11-04 [2] CRAN (R 4.0.5)
#> colorspace 2.0-1 2021-05-04 [1] CRAN (R 4.0.5)
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#> infer * 0.5.4.9000 2021-03-27 [1] Github (tidymodels/infer@66d24a0)
#> ipred 0.9-11 2021-03-12 [1] CRAN (R 4.0.4)
#> iterators 1.0.13 2020-10-15 [1] CRAN (R 4.0.3)
#> jsonlite 1.7.2 2020-12-09 [1] CRAN (R 4.0.3)
#> knitr 1.33 2021-04-24 [1] CRAN (R 4.0.5)
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#> prodlim 2019.11.13 2019-11-17 [1] CRAN (R 4.0.4)
#> ps 1.6.0 2021-02-28 [1] CRAN (R 4.0.5)
#> purrr * 0.3.4 2020-04-17 [1] CRAN (R 4.0.3)
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#> Rcpp 1.0.6 2021-01-15 [1] CRAN (R 4.0.4)
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配方步骤 需要有一个 tunable S3 方法用于任何你想调整的参数， 比如 digits.
查看 this article about creating your own recipe step, but I don't think you need to create your own recipe step altogether; you only need to make a tunable method for the step you are using, which is under "Other step methods"。