Tidymodels 调整配方参数

Question

使用 tidymodels，我真的很喜欢不仅可以调整模型参数，还可以调整一些食谱步骤的可能性。例如 step_pls() 中的组件数。问题是我在限制可能值的范围方面遇到了麻烦。例如，如果我想使用 step_umap，我想将搜索 space 限制为 2:5 组件。当我用 step_umap() 替换 step_pls() 时，以下代码导致会话崩溃。它试图用大约 50 个组件构建 umap... 所以基本上，我的问题是，在使用 grid_random 或 grid_max_entropy 时，如何限制特定调整参数的搜索范围？

注意：还尝试了类似 param_grid%>%grid_random(size=5,num_comp() %>% range_set(c(3, 5))) 的方法。但是好像被忽略了。

谢谢

# Load Packages -----------------------------------------------------------
require(tidyverse)
require(lubridate)
require(tidymodels)
require(rsample)
require(themis)
require(recipes)
require(embed)
# Load Data ---------------------------------------------------------------
data<-read_csv("....data.csv")

# Modelling - Data Partition ----------------------------------------------
split_prop <- 0.80
init_split <- initial_time_split(data, prop = split_prop)

set_train<-training(init_split)
set_test<-testing(init_split)

# Modelling - Resamples ---------------------------------------------------
valid_folds <- rsample::vfold_cv(set_train,v=5)

# Modelling - Data Transf -------------------------------------------------
recip_train <- recipe(label ~ .,
                      data = set_train)%>%
  step_normalize(all_predictors())%>%
  step_pls(all_predictors(),outcome = "label",num_comp = tune())

# Modelling - Model Specs ---------------------------------------------------
model_glm <- linear_reg()%>%
  set_args(penalty=tune(),
           mixture=tune())%>%
  set_mode("regression") %>%
  set_engine("glmnet")

# Workflow ------------------------------------------------------------------
wflw <- workflow() %>%
    add_recipe(recip_train) %>%
    add_model(model_glm)

# Modelling - Tuning Control -------------------------------------------------
ctr_tune <- control_grid(
  verbose = TRUE,
  allow_par = TRUE,
  extract = NULL,
  save_pred = TRUE,
  pkgs = NULL
  )

param_grid<-wflw %>%
    parameters()%>% 
    finalize(set_train)%>%  
    grid_max_entropy(size = 5)

# Modelling - Tuning ---------------------------------------------------------
tuning <- tune_grid(object = wflw,
                    resamples =  valid_folds,
                    grid = param_grid,
                    control = ctr_tune,
                    metrics = metric_set(rmse))

Answer 1

如果您想尝试 num_comp 的特定范围，我不会费心进入工作流程并获取参数等。我会设置调整网格直接参数：

library(dials)
#> Loading required package: scales
grid_max_entropy(penalty(),
                 mixture(),
                 num_comp(range = c(2, 5)),
                 size = 5)
#> # A tibble: 5 x 3
#>         penalty mixture num_comp
#>           <dbl>   <dbl>    <int>
#> 1 0.00161        0.721         5
#> 2 0.751          0.376         4
#> 3 0.00000000974  0.395         3
#> 4 0.000107       0.0747        4
#> 5 0.0000000451   0.906         3

^{由 reprex package (v0.3.0)}

于 2020-07-19 创建

Tidymodels 调整配方参数

Tidymodels Tuning Recipe Parameters

r

tidymodels

r-recipes