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社区首页 >问答首页 >将带有分类变量的Tidymodels glmnet模型传递到gt汇总:未识别配方转换变量

问将带有分类变量的Tidymodels glmnet模型传递到gt汇总:未识别配方转换变量
EN

Stack Overflow用户
提问于 2022-06-18 08:25:08
回答 1查看 101关注 0票数 0

在tidymodels模型中的分类数据是如何被by汇总整理的，正在发生一些事情。tidymodels团队认为，gt汇总似乎没有考虑到通过从配方中进行预处理从原始变量进行的转换，或者整理工作根本就没有那么好？错误的重述如下。任何帮助都是非常感谢的！

代码语言：javascript
复制
    library(tidymodels)

    data(penguins)

    my_split <- penguins %>%
      na.omit() %>%
      initial_split()
    
    rec <- recipe(sex ~ species + bill_length_mm + bill_depth_mm,
      data = penguins
    ) %>%
      step_dummy(species)
    
    glmnet_spec <- logistic_reg(penalty = 0.1, mixture = 1) %>%
      set_engine("glmnet")
    
    glmnet_fit <-
      workflow(rec, glmnet_spec) %>%
      last_fit(my_split)
    
    
    extract_workflow(glmnet_fit) %>%
      gtsummary::tbl_regression(exponentiate = TRUE) %>%
      gtsummary::as_kable()
    #> Extracting {workflows} model fit with `workflows::extract_fit_parsnip(x) %>% tbl_regression(...)`
    #> Extracting {parsnip} model fit with `tbl_regression(x = x$fit, ...)`
    #> x Unable to identify the list of variables.
    #> 
    #> This is usually due to an error calling `stats::model.frame(x)`or `stats::model.matrix(x)`.
    #> It could be the case if that type of model does not implement these methods.
    #> Rarely, this error may occur if the model object was created within
    #> a functional programming framework (e.g. using `lappy()`, `purrr::map()`, etc.).
    ```
    
    | **Characteristic** | **exp(Beta)** |
    |:-------------------|:-------------:|
    | (Intercept)        |               |
    | (Intercept)        |     0.07      |
    | (Intercept)        |     -1.11     |
    | (Intercept)        |     -2.38     |
    | (Intercept)        |     -3.56     |
    | (Intercept)        |     -4.67     |
    | (Intercept)        |     -5.73     |
    | (Intercept)        |     -6.75     |
    | (Intercept)        |     -7.71     |
    | (Intercept)        |     -9.41     |
    | (Intercept)        |     -11.2     |
    | (Intercept)        |     -12.9     |
    | (Intercept)        |     -14.6     |
    | (Intercept)        |     -16.3     |
    | (Intercept)        |     -18.0     |
    | (Intercept)        |     -19.6     |
    | (Intercept)        |     -21.3     |
    | (Intercept)        |     -22.9     |
    | (Intercept)        |     -24.6     |
    | (Intercept)        |     -26.2     |
    | (Intercept)        |     -27.8     |
    | (Intercept)        |     -29.4     |
    | (Intercept)        |     -30.9     |
    | (Intercept)        |     -32.5     |
    | (Intercept)        |     -34.0     |
    | (Intercept)        |     -35.5     |
    | (Intercept)        |     -37.0     |
    | (Intercept)        |     -38.4     |
    | (Intercept)        |     -39.9     |
    | (Intercept)        |     -41.2     |
    | (Intercept)        |     -42.6     |
    | (Intercept)        |     -43.9     |
    | (Intercept)        |     -45.2     |
    | (Intercept)        |     -46.4     |
    | (Intercept)        |     -47.6     |
    | (Intercept)        |     -48.8     |
    | (Intercept)        |     -49.9     |
    | (Intercept)        |     -51.0     |
    | (Intercept)        |     -52.0     |
    | (Intercept)        |     -53.0     |
    | (Intercept)        |     -53.9     |
    | (Intercept)        |     -54.8     |
    | (Intercept)        |     -55.6     |
    | (Intercept)        |     -56.4     |
    | (Intercept)        |     -57.1     |
    | (Intercept)        |     -57.8     |
    | (Intercept)        |     -58.4     |
    | (Intercept)        |     -59.0     |
    | (Intercept)        |     -59.6     |
    | (Intercept)        |     -60.1     |
    | (Intercept)        |     -60.6     |
    | (Intercept)        |     -61.0     |
    | (Intercept)        |     -61.5     |
    | (Intercept)        |     -61.8     |
    | (Intercept)        |     -62.2     |
    | (Intercept)        |     -62.5     |
    | (Intercept)        |     -62.8     |
    | (Intercept)        |     -63.1     |
    | (Intercept)        |     -63.4     |
    | (Intercept)        |     -63.6     |
    | (Intercept)        |     -63.8     |
    | (Intercept)        |     -64.0     |
    | (Intercept)        |     -64.2     |
    | (Intercept)        |     -64.4     |
    | (Intercept)        |     -64.5     |
    | (Intercept)        |     -64.7     |
    | (Intercept)        |     -64.8     |
    | (Intercept)        |     -64.9     |
    | (Intercept)        |     -65.0     |
    | (Intercept)        |     -65.1     |
    | bill_length_mm     |               |
    | bill_length_mm     |     0.01      |
    | bill_length_mm     |     0.03      |
    | bill_length_mm     |     0.04      |
    | bill_length_mm     |     0.05      |
    | bill_length_mm     |     0.06      |
    | bill_length_mm     |     0.08      |
    | bill_length_mm     |     0.09      |
    | bill_length_mm     |     0.11      |
    | bill_length_mm     |     0.13      |
    | bill_length_mm     |     0.15      |
    | bill_length_mm     |     0.17      |
    | bill_length_mm     |     0.19      |
    | bill_length_mm     |     0.21      |
    | bill_length_mm     |     0.23      |
    | bill_length_mm     |     0.25      |
    | bill_length_mm     |     0.27      |
    | bill_length_mm     |     0.28      |
    | bill_length_mm     |     0.30      |
    | bill_length_mm     |     0.32      |
    | bill_length_mm     |     0.34      |
    | bill_length_mm     |     0.36      |
    | bill_length_mm     |     0.38      |
    | bill_length_mm     |     0.40      |
    | bill_length_mm     |     0.41      |
    | bill_length_mm     |     0.43      |
    | bill_length_mm     |     0.45      |
    | bill_length_mm     |     0.47      |
    | bill_length_mm     |     0.48      |
    | bill_length_mm     |     0.50      |
    | bill_length_mm     |     0.51      |
    | bill_length_mm     |     0.53      |
    | bill_length_mm     |     0.54      |
    | bill_length_mm     |     0.55      |
    | bill_length_mm     |     0.56      |
    | bill_length_mm     |     0.57      |
    | bill_length_mm     |     0.58      |
    | bill_length_mm     |     0.59      |
    | bill_length_mm     |     0.59      |
    | bill_length_mm     |     0.60      |
    | bill_length_mm     |     0.61      |
    | bill_length_mm     |     0.62      |
    | bill_length_mm     |     0.62      |
    | bill_length_mm     |     0.63      |
    | bill_length_mm     |     0.64      |
    | bill_length_mm     |     0.64      |
    | bill_length_mm     |     0.65      |
    | bill_length_mm     |     0.65      |
    | bill_length_mm     |     0.66      |
    | bill_length_mm     |     0.66      |
    | bill_length_mm     |     0.66      |
    | bill_length_mm     |     0.67      |
    | bill_length_mm     |     0.67      |
    | bill_length_mm     |     0.67      |
    | bill_length_mm     |     0.68      |
    | bill_length_mm     |     0.68      |
    | bill_length_mm     |     0.68      |
    | bill_length_mm     |     0.68      |
    | bill_length_mm     |     0.69      |
    | bill_length_mm     |     0.69      |
    | bill_length_mm     |     0.69      |
    | bill_length_mm     |     0.69      |
    | bill_length_mm     |     0.69      |
    | bill_length_mm     |     0.69      |
    | bill_length_mm     |     0.70      |
    | bill_length_mm     |     0.70      |
    | bill_length_mm     |     0.70      |
    | bill_length_mm     |     0.70      |
    | bill_length_mm     |     0.70      |
    | bill_depth_mm      |               |
    | bill_depth_mm      |     0.03      |
    | bill_depth_mm      |     0.07      |
    | bill_depth_mm      |     0.11      |
    | bill_depth_mm      |     0.14      |
    | bill_depth_mm      |     0.17      |
    | bill_depth_mm      |     0.21      |
    | bill_depth_mm      |     0.24      |
    | bill_depth_mm      |     0.29      |
    | bill_depth_mm      |     0.34      |
    | bill_depth_mm      |     0.39      |
    | bill_depth_mm      |     0.44      |
    | bill_depth_mm      |     0.49      |
    | bill_depth_mm      |     0.54      |
    | bill_depth_mm      |     0.59      |
    | bill_depth_mm      |     0.64      |
    | bill_depth_mm      |     0.69      |
    | bill_depth_mm      |     0.74      |
    | bill_depth_mm      |     0.79      |
    | bill_depth_mm      |     0.83      |
    | bill_depth_mm      |     0.88      |
    | bill_depth_mm      |     0.93      |
    | bill_depth_mm      |     0.97      |
    | bill_depth_mm      |     1.02      |
    | bill_depth_mm      |     1.06      |
    | bill_depth_mm      |     1.11      |
    | bill_depth_mm      |     1.15      |
    | bill_depth_mm      |     1.19      |
    | bill_depth_mm      |     1.23      |
    | bill_depth_mm      |     1.27      |
    | bill_depth_mm      |     1.31      |
    | bill_depth_mm      |     1.35      |
    | bill_depth_mm      |     1.40      |
    | bill_depth_mm      |     1.44      |
    | bill_depth_mm      |     1.49      |
    | bill_depth_mm      |     1.53      |
    | bill_depth_mm      |     1.57      |
    | bill_depth_mm      |     1.61      |
    | bill_depth_mm      |     1.64      |
    | bill_depth_mm      |     1.68      |
    | bill_depth_mm      |     1.71      |
    | bill_depth_mm      |     1.74      |
    | bill_depth_mm      |     1.77      |
    | bill_depth_mm      |     1.79      |
    | bill_depth_mm      |     1.82      |
    | bill_depth_mm      |     1.84      |
    | bill_depth_mm      |     1.86      |
    | bill_depth_mm      |     1.88      |
    | bill_depth_mm      |     1.90      |
    | bill_depth_mm      |     1.92      |
    | bill_depth_mm      |     1.93      |
    | bill_depth_mm      |     1.95      |
    | bill_depth_mm      |     1.96      |
    | bill_depth_mm      |     1.98      |
    | bill_depth_mm      |     1.99      |
    | bill_depth_mm      |     2.00      |
    | bill_depth_mm      |     2.01      |
    | bill_depth_mm      |     2.02      |
    | bill_depth_mm      |     2.03      |
    | bill_depth_mm      |     2.04      |
    | bill_depth_mm      |     2.04      |
    | bill_depth_mm      |     2.05      |
    | bill_depth_mm      |     2.05      |
    | bill_depth_mm      |     2.06      |
    | bill_depth_mm      |     2.07      |
    | bill_depth_mm      |     2.07      |
    | bill_depth_mm      |     2.07      |
    | bill_depth_mm      |     2.08      |
    | bill_depth_mm      |     2.08      |
    | species_Chinstrap  |               |
    | species_Chinstrap  |     -0.25     |
    | species_Chinstrap  |     -0.53     |
    | species_Chinstrap  |     -0.80     |
    | species_Chinstrap  |     -1.06     |
    | species_Chinstrap  |     -1.31     |
    | species_Chinstrap  |     -1.56     |
    | species_Chinstrap  |     -1.81     |
    | species_Chinstrap  |     -2.05     |
    | species_Chinstrap  |     -2.29     |
    | species_Chinstrap  |     -2.53     |
    | species_Chinstrap  |     -2.76     |
    | species_Chinstrap  |     -3.00     |
    | species_Chinstrap  |     -3.22     |
    | species_Chinstrap  |     -3.45     |
    | species_Chinstrap  |     -3.67     |
    | species_Chinstrap  |     -3.89     |
    | species_Chinstrap  |     -4.11     |
    | species_Chinstrap  |     -4.32     |
    | species_Chinstrap  |     -4.53     |
    | species_Chinstrap  |     -4.73     |
    | species_Chinstrap  |     -4.93     |
    | species_Chinstrap  |     -5.12     |
    | species_Chinstrap  |     -5.31     |
    | species_Chinstrap  |     -5.47     |
    | species_Chinstrap  |     -5.61     |
    | species_Chinstrap  |     -5.73     |
    | species_Chinstrap  |     -5.86     |
    | species_Chinstrap  |     -5.98     |
    | species_Chinstrap  |     -6.09     |
    | species_Chinstrap  |     -6.20     |
    | species_Chinstrap  |     -6.30     |
    | species_Chinstrap  |     -6.40     |
    | species_Chinstrap  |     -6.50     |
    | species_Chinstrap  |     -6.58     |
    | species_Chinstrap  |     -6.67     |
    | species_Chinstrap  |     -6.75     |
    | species_Chinstrap  |     -6.82     |
    | species_Chinstrap  |     -6.89     |
    | species_Chinstrap  |     -6.95     |
    | species_Chinstrap  |     -7.01     |
    | species_Chinstrap  |     -7.07     |
    | species_Chinstrap  |     -7.12     |
    | species_Chinstrap  |     -7.17     |
    | species_Chinstrap  |     -7.22     |
    | species_Chinstrap  |     -7.26     |
    | species_Chinstrap  |     -7.30     |
    | species_Chinstrap  |     -7.33     |
    | species_Chinstrap  |     -7.37     |
    | species_Chinstrap  |     -7.40     |
    | species_Chinstrap  |     -7.42     |
    | species_Chinstrap  |     -7.45     |
    | species_Chinstrap  |     -7.47     |
    | species_Chinstrap  |     -7.49     |
    | species_Chinstrap  |     -7.52     |
    | species_Chinstrap  |     -7.53     |
    | species_Chinstrap  |     -7.55     |
    | species_Chinstrap  |     -7.57     |
    | species_Chinstrap  |     -7.58     |
    | species_Chinstrap  |     -7.59     |
    | species_Chinstrap  |     -7.60     |
    | species_Chinstrap  |     -7.61     |
    | species_Gentoo     |               |
    | species_Gentoo     |     0.03      |
    | species_Gentoo     |     0.10      |
    | species_Gentoo     |     0.17      |
    | species_Gentoo     |     0.24      |
    | species_Gentoo     |     0.31      |
    | species_Gentoo     |     0.37      |
    | species_Gentoo     |     0.43      |
    | species_Gentoo     |     0.49      |
    | species_Gentoo     |     0.54      |
    | species_Gentoo     |     0.59      |
    | species_Gentoo     |     0.63      |
    | species_Gentoo     |     0.68      |
    | species_Gentoo     |     0.72      |
    | species_Gentoo     |     0.76      |
    | species_Gentoo     |     0.79      |
    | species_Gentoo     |     0.82      |
    | species_Gentoo     |     0.85      |
    | species_Gentoo     |     0.88      |
    | species_Gentoo     |     0.91      |
    | species_Gentoo     |     0.93      |
    | species_Gentoo     |     0.95      |
    | species_Gentoo     |     0.97      |
    | species_Gentoo     |     0.99      |
    | species_Gentoo     |     1.01      |
    | species_Gentoo     |     1.03      |
    | species_Gentoo     |     1.04      |
    | species_Gentoo     |     1.06      |
    | species_Gentoo     |     1.07      |
    | species_Gentoo     |     1.08      |
    | species_Gentoo     |     1.09      |
    | species_Gentoo     |     1.10      |
    | species_Gentoo     |     1.11      |
    | species_Gentoo     |     1.12      |
    | species_Gentoo     |     1.12      |
    | species_Gentoo     |     1.13      |
    | species_Gentoo     |     1.14      |
    | species_Gentoo     |     1.14      |
    | species_Gentoo     |     1.15      |
    
    <sup>Created on 2022-06-18 by the [reprex package](https://reprex.tidyverse.org) (v2.0.1)</sup>
    
    <details style="margin-bottom:10px;">
    <summary>
    Session info
    </summary>
    
```r
代码语言：javascript
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sessioninfo::session_info()
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#> - Session info ---------------------------------------------------------------
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#>  setting  value
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#>  version  R version 4.1.3 (2022-03-10)
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#>  os       Windows 10 x64 (build 22000)
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#>  system   x86_64, mingw32
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#>  ui       RTerm
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#>  language (EN)
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#>  collate  English_United Kingdom.1252
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#>  ctype    English_United Kingdom.1252
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#>  tz       Europe/London
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#>  date     2022-06-18
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#>  pandoc   2.18 @ C:/PROGRA~3/chocolatey/bin/ (via rmarkdown)
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#>
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#> - Packages -------------------------------------------------------------------
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#>  package       * version    date (UTC) lib source
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#>  assertthat      0.2.1      2019-03-21 [1] CRAN (R 4.1.2)
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#>  backports       1.4.1      2021-12-13 [1] CRAN (R 4.1.2)
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#>  broom         * 0.8.0      2022-04-13 [1] CRAN (R 4.1.3)
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#>  broom.helpers   1.6.0      2022-01-12 [1] CRAN (R 4.1.2)
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#>  class           7.3-20     2022-01-13 [1] CRAN (R 4.1.2)
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#>  cli             3.2.0      2022-02-14 [1] CRAN (R 4.1.2)
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#>  codetools       0.2-18     2020-11-04 [2] CRAN (R 4.1.3)
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#>  colorspace      2.0-3      2022-02-21 [1] CRAN (R 4.1.3)
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#>  crayon          1.5.1      2022-03-26 [1] CRAN (R 4.1.3)
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#>  DBI             1.1.2      2021-12-20 [1] CRAN (R 4.1.2)
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#>  dials         * 0.1.0      2022-01-31 [1] CRAN (R 4.1.2)
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#>  DiceDesign      1.9        2021-02-13 [1] CRAN (R 4.1.2)
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#>  digest          0.6.29     2021-12-01 [1] CRAN (R 4.1.2)
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#>  dplyr         * 1.0.8      2022-02-08 [1] CRAN (R 4.1.2)
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#>  ellipsis        0.3.2      2021-04-29 [1] CRAN (R 4.1.2)
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#>  evaluate        0.15       2022-02-18 [1] CRAN (R 4.1.2)
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#>  fansi           1.0.3      2022-03-24 [1] CRAN (R 4.1.3)
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#>  fastmap         1.1.0      2021-01-25 [1] CRAN (R 4.1.2)
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#>  foreach         1.5.2      2022-02-02 [1] CRAN (R 4.1.2)
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#>  fs              1.5.2      2021-12-08 [1] CRAN (R 4.1.2)
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#>  furrr           0.2.3      2021-06-25 [1] CRAN (R 4.1.2)
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#>  future          1.24.0     2022-02-19 [1] CRAN (R 4.1.3)
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#>  future.apply    1.8.1      2021-08-10 [1] CRAN (R 4.1.2)
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#>  generics        0.1.2      2022-01-31 [1] CRAN (R 4.1.2)
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#>  ggplot2       * 3.3.5      2021-06-25 [1] CRAN (R 4.1.2)
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#>  glmnet        * 4.1-4      2022-04-15 [1] CRAN (R 4.1.3)
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#>  globals         0.14.0     2020-11-22 [1] CRAN (R 4.1.1)
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#>  glue            1.6.2      2022-02-24 [1] CRAN (R 4.1.3)
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#>  gower           1.0.0      2022-02-03 [1] CRAN (R 4.1.2)
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#>  GPfit           1.0-8      2019-02-08 [1] CRAN (R 4.1.2)
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#>  gt              0.6.0      2022-05-24 [1] CRAN (R 4.1.3)
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#>  gtable          0.3.0      2019-03-25 [1] CRAN (R 4.1.2)
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#> ------------------------------------------------------------------------------
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```javascript

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r
tidymodels
gtsummary
EN

回答 1

Stack Overflow用户

发布于 2022-07-13 14:13:09

(小编辑)

它看起来像是gt汇总中的一个问题：

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library(tidymodels)

data(penguins)

penguins <- penguins %>% na.omit()
my_split <- penguins %>%
  initial_split()

rec <- recipe(sex ~ species + bill_length_mm + bill_depth_mm,
              data = penguins
) %>%
  step_dummy(species)

x <- prep(rec) %>% bake(-sex, new_data = NULL, composition = "matrix")
y <- penguins$sex

glmn_fit <- glmnet::glmnet(x, y, alpha = 1, family = "binomial")

glmn_fit %>%
  gtsummary::tbl_regression(exponentiate = TRUE) 
#> ✖ Unable to identify the list of variables.
#> 
#> This is usually due to an error calling `stats::model.frame(x)`or `stats::model.matrix(x)`.
#> It could be the case if that type of model does not implement these methods.
#> Rarely, this error may occur if the model object was created within
#> a functional programming framework (e.g. using `lappy()`, `purrr::map()`, etc.).

(删除相同的html结果)

它们没有用于glmnet的tbl_regression()方法，因此将调用默认方法。对于这种类型的对象来说，这不是很好。

票数 0
EN
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：

https://stackoverflow.com/questions/72667819

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