tidymodels bake：错误：请将数据集传递给`new_data`

如何解决tidymodels bake：错误：请将数据集传递给`new_data`

我在recipe()软件包中使用tidymodels函数来估算缺失值并修复不平衡数据。

这是我的数据；

mer_df <- mer2 %>%
  filter(!is.na(laststagestatus2)) %>% 
  select(Id,Age_Range__c,Gender__c,numberoflead,leadduration,firsttouch,lasttouch,laststagestatus2)%>%
  mutate_if(is.character,factor) %>%
  mutate_if(is.logical,as.integer)


# A tibble: 197,836 x 8
   Id    Age_Range__c Gender__c numberoflead leadduration firsttouch lasttouch
   <fct> <fct>        <fct>            <int>        <dbl> <fct>      <fct>    
 1 0010~ NA           NA                   2     5.99     Dealer IB~ Walk in  
 2 0010~ NA           NA                   1     0        Online Se~ Online S~
 3 0010~ NA           NA                   1     0        Walk in    Walk in  
 4 0010~ NA           NA                   1     0        Online Se~ Online S~
 5 0010~ NA           NA                   2     0.0128   Dealer IB~ Dealer I~
 6 0010~ NA           NA                   1     0        OB Call    OB Call  
 7 0010~ NA           NA                   1     0        Dealer IB~ Dealer I~
 8 0010~ NA           NA                   4    73.9      Dealer IB~ Walk in  
 9 0010~ NA           Male                24     0.000208 OB Call    OB Call  
10 0010~ NA           NA                  18     0.000150 OB Call    OB Call  
# ... with 197,826 more rows,and 1 more variable: laststagestatus2 <fct>

这是我的代码；

mer_rec <- recipe(laststagestatus2 ~ .,data = mer_train)%>%
  step_medianimpute(numberoflead,leadduration)%>%
  step_knnimpute(Gender__c,fisrsttouch,lasttouch) %>% 
  step_other(Id,firsttouch) %>% 
  step_other(Id,lasttouch) %>% 
  step_dummy(all_nominal(),-laststagestatus2) %>% 
  step_smote(laststagestatus2)
mer_rec
mer_rec %>% prep()

直到这里为止一切正常；

Data Recipe

Inputs:

      role #variables
   outcome          1
 predictor          7

Training data contained 148377 data points and 147597 incomplete rows. 

    Operations:
    
    Median Imputation for 2 items [trained]
    K-nearest neighbor imputation for Id,... [trained]
    Collapsing factor levels for Id,firsttouch [trained]
    Collapsing factor levels for Id,lasttouch [trained]
    Dummy variables from Id,... [trained]
    SMOTE based on laststagestatus2 [trained]

但是当ı运行bake()函数时会提示错误；

mer_rec %>% prep() %>% bake(new_data=NULL) %>% count(laststagestatus2)
Error: Please pass a data set to `new_data`.

有人可以帮我解决我在这里想念的东西吗？

解决方法

配方的开发版本中有一个修复程序可以使它正常运行。您可以通过以下方式安装：

devtools::install_github("tidymodels/recipes")

然后您可以bake()和new_data = NULL来获取转换后的训练数据。

library(tidymodels)
data(ames)
ames <- mutate(ames,Sale_Price = log10(Sale_Price))

set.seed(123)
ames_split <- initial_split(ames,prob = 0.80,strata = Sale_Price)
ames_train <- training(ames_split)
ames_test  <-  testing(ames_split)

ames_rec <- 
  recipe(Sale_Price ~ Neighborhood + Gr_Liv_Area + Year_Built + Bldg_Type + 
           Latitude + Longitude,data = ames_train) %>%
  step_log(Gr_Liv_Area,base = 10) %>% 
  step_other(Neighborhood,threshold = 0.01) %>% 
  step_dummy(all_nominal()) %>% 
  step_interact( ~ Gr_Liv_Area:starts_with("Bldg_Type_") ) %>% 
  step_ns(Latitude,Longitude,deg_free = 20)

ames_rec %>% prep() %>% bake(new_data = NULL)
#> # A tibble: 2,199 x 71
#>    Gr_Liv_Area Year_Built Sale_Price Neighborhood_Co… Neighborhood_Ol…
#>          <dbl>      <int>      <dbl>            <dbl>            <dbl>
#>  1        3.22       1960       5.33                0                0
#>  2        2.95       1961       5.02                0                0
#>  3        3.12       1958       5.24                0                0
#>  4        3.21       1997       5.28                0                0
#>  5        3.21       1998       5.29                0                0
#>  6        3.13       2001       5.33                0                0
#>  7        3.11       1992       5.28                0                0
#>  8        3.21       1995       5.37                0                0
#>  9        3.22       1993       5.25                0                0
#> 10        3.17       1998       5.26                0                0
#> # … with 2,189 more rows,and 66 more variables: Neighborhood_Edwards <dbl>,#> #   Neighborhood_Somerset <dbl>,Neighborhood_Northridge_Heights <dbl>,#> #   Neighborhood_Gilbert <dbl>,Neighborhood_Sawyer <dbl>,#> #   Neighborhood_Northwest_Ames <dbl>,Neighborhood_Sawyer_West <dbl>,#> #   Neighborhood_Mitchell <dbl>,Neighborhood_Brookside <dbl>,#> #   Neighborhood_Crawford <dbl>,Neighborhood_Iowa_DOT_and_Rail_Road <dbl>,#> #   Neighborhood_Timberland <dbl>,Neighborhood_Northridge <dbl>,#> #   Neighborhood_Stone_Brook <dbl>,#> #   Neighborhood_South_and_West_of_Iowa_State_University <dbl>,#> #   Neighborhood_Clear_Creek <dbl>,Neighborhood_Meadow_Village <dbl>,#> #   Neighborhood_other <dbl>,Bldg_Type_TwoFmCon <dbl>,Bldg_Type_Duplex <dbl>,#> #   Bldg_Type_Twnhs <dbl>,Bldg_Type_TwnhsE <dbl>,#> #   Gr_Liv_Area_x_Bldg_Type_TwoFmCon <dbl>,#> #   Gr_Liv_Area_x_Bldg_Type_Duplex <dbl>,Gr_Liv_Area_x_Bldg_Type_Twnhs <dbl>,#> #   Gr_Liv_Area_x_Bldg_Type_TwnhsE <dbl>,Latitude_ns_01 <dbl>,#> #   Latitude_ns_02 <dbl>,Latitude_ns_03 <dbl>,Latitude_ns_04 <dbl>,#> #   Latitude_ns_05 <dbl>,Latitude_ns_06 <dbl>,Latitude_ns_07 <dbl>,#> #   Latitude_ns_08 <dbl>,Latitude_ns_09 <dbl>,Latitude_ns_10 <dbl>,#> #   Latitude_ns_11 <dbl>,Latitude_ns_12 <dbl>,Latitude_ns_13 <dbl>,#> #   Latitude_ns_14 <dbl>,Latitude_ns_15 <dbl>,Latitude_ns_16 <dbl>,#> #   Latitude_ns_17 <dbl>,Latitude_ns_18 <dbl>,Latitude_ns_19 <dbl>,#> #   Latitude_ns_20 <dbl>,Longitude_ns_01 <dbl>,Longitude_ns_02 <dbl>,#> #   Longitude_ns_03 <dbl>,Longitude_ns_04 <dbl>,Longitude_ns_05 <dbl>,#> #   Longitude_ns_06 <dbl>,Longitude_ns_07 <dbl>,Longitude_ns_08 <dbl>,#> #   Longitude_ns_09 <dbl>,Longitude_ns_10 <dbl>,Longitude_ns_11 <dbl>,#> #   Longitude_ns_12 <dbl>,Longitude_ns_13 <dbl>,Longitude_ns_14 <dbl>,#> #   Longitude_ns_15 <dbl>,Longitude_ns_16 <dbl>,Longitude_ns_17 <dbl>,#> #   Longitude_ns_18 <dbl>,Longitude_ns_19 <dbl>,Longitude_ns_20 <dbl>

^{由reprex package（v0.3.0.9001）于2020-10-12创建}

如果无法从GitHub安装软件包，则可以use juice() to do the same thing。