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tune engine specific arguments: error on finalize_workflow #195

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AlbertoAlmuinha opened this issue Aug 9, 2022 · 0 comments
Closed

tune engine specific arguments: error on finalize_workflow #195

AlbertoAlmuinha opened this issue Aug 9, 2022 · 0 comments

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@AlbertoAlmuinha
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The problem

I'm having trouble when trying to finish the workflow after applying the tune_grid function through worfklow_map. When I extract the best hyperparameters and introduce them in the finalize_workflow() function I get the following error as one of them is engine specific.

Here is a related problem with a solution: tidymodels/tune#254

I think it is necessary to change the update method of the definition of the arima model. Not sure if maybe others as well, I just try arima.

Error in `parsnip::update_dot_check()` at modeltime/R/parsnip-arima_reg.R:258:4:
! Extra arguments will be ignored: `include.mean`

Reproducible example

``` r
library(tidymodels)
#> Warning: package 'tidymodels' was built under R version 4.1.3
#> Warning: package 'broom' was built under R version 4.1.3
#> Warning: package 'dials' was built under R version 4.1.3
#> Warning: package 'dplyr' was built under R version 4.1.3
#> Warning: package 'ggplot2' was built under R version 4.1.3
#> Warning: package 'infer' was built under R version 4.1.3
#> Warning: package 'modeldata' was built under R version 4.1.3
#> Warning: package 'parsnip' was built under R version 4.1.3
#> Warning: package 'recipes' was built under R version 4.1.3
#> Warning: package 'rsample' was built under R version 4.1.3
#> Warning: package 'tibble' was built under R version 4.1.3
#> Warning: package 'tidyr' was built under R version 4.1.3
#> Warning: package 'tune' was built under R version 4.1.3
#> Warning: package 'workflows' was built under R version 4.1.3
#> Warning: package 'workflowsets' was built under R version 4.1.3
#> Warning: package 'yardstick' was built under R version 4.1.3
library(modeltime)
library(modeltime.resample)
library(timetk)
#> Warning: package 'timetk' was built under R version 4.1.3
library(tidyverse)

full_data_tbl <- walmart_sales_weekly %>%
  select(id, Date, Weekly_Sales) %>%
  
  # Apply Group-wise Time Series Manipulations
  group_by(id) %>%
  future_frame(
    .date_var   = Date,
    .length_out = "3 months",
    .bind_data  = TRUE
  ) %>%
  ungroup() %>%
  
  # Consolidate IDs
  mutate(id = fct_drop(id))

# Training Data
data_prepared_tbl <- full_data_tbl %>%
  filter(!is.na(Weekly_Sales))

walmart_tscv <- data_prepared_tbl %>%
  time_series_cv(
    date_var    = Date, 
    assess      = "3 months",
    skip        = "3 months",
    cumulative  = TRUE,
    slice_limit = 6
  )
#> Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
#> Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.

recipe_spec <- recipe(Weekly_Sales ~ ., 
                      data = training(walmart_tscv$splits[[1]])) %>%
  step_filter(id == "1_1") %>%
  step_rm(id) 


arima_spec <- arima_reg(non_seasonal_ar = tune(), 
                        non_seasonal_differences = tune(),
                        non_seasonal_ma = tune()) %>%
              set_engine("arima", include.mean = tune())


wfset <- workflow_set(
          preproc = list(rec = recipe_spec),
          models = list(arima = arima_spec),
          cross = TRUE
        ) %>%
        option_add(grid = crossing(non_seasonal_ar = 1:1, 
                                   non_seasonal_differences = 1:1, 
                                   non_seasonal_ma = 1:4, 
                                   include.mean = 1:1) %>%
                     mutate(include.mean = TRUE))


grid_results <- 
  wfset %>% 
  workflow_map("tune_grid", 
               resamples = walmart_tscv, 
               seed = 123,
               metrics = default_forecast_accuracy_metric_set(), 
               verbose = TRUE)
#> i 1 of 1 tuning:     rec_arima
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 13 observations per 1 quarter
#> frequency = 12.5 observations per 1 quarter
#> frequency = 12.5 observations per 1 quarter
#> frequency = 12.5 observations per 1 quarter
#> frequency = 12.5 observations per 1 quarter
#> v 1 of 1 tuning:     rec_arima (10.4s)


best_results <- 
  grid_results %>% 
  extract_workflow_set_result("rec_arima") %>% 
  select_best(metric = "rmse")


test_results <- 
  grid_results %>% 
  extract_workflow("rec_arima") %>% 
  finalize_workflow(best_results)
#> Error in `parsnip::update_dot_check()` at modeltime/R/parsnip-arima_reg.R:258:4:
#> ! Extra arguments will be ignored: `include.mean`

Created on 2022-08-09 by the reprex package (v2.0.1)

Session info 
sessioninfo::session_info()
#> - Session info ---------------------------------------------------------------
#>  setting  value
#>  version  R version 4.1.0 (2021-05-18)
#>  os       Windows 10 x64 (build 19043)
#>  system   x86_64, mingw32
#>  ui       RTerm
#>  language (EN)
#>  collate  Spanish_Spain.1252
#>  ctype    Spanish_Spain.1252
#>  tz       Europe/Paris
#>  date     2022-08-09
#>  pandoc   2.18 @ C:/Program Files/RStudio/bin/quarto/bin/tools/ (via rmarkdown)
#> 
#> - Packages -------------------------------------------------------------------
#>  package            * version    date (UTC) lib source
#>  assertthat           0.2.1      2019-03-21 [1] CRAN (R 4.1.0)
#>  backports            1.2.1      2020-12-09 [1] CRAN (R 4.1.0)
#>  broom              * 1.0.0      2022-07-01 [1] CRAN (R 4.1.3)
#>  cellranger           1.1.0      2016-07-27 [1] CRAN (R 4.1.0)
#>  class                7.3-19     2021-05-03 [2] CRAN (R 4.1.0)
#>  cli                  3.3.0      2022-04-25 [1] CRAN (R 4.1.3)
#>  codetools            0.2-18     2020-11-04 [2] CRAN (R 4.1.0)
#>  colorspace           2.0-1      2021-05-04 [1] CRAN (R 4.1.0)
#>  crayon               1.4.1      2021-02-08 [1] CRAN (R 4.1.0)
#>  curl                 4.3.1      2021-04-30 [1] CRAN (R 4.1.0)
#>  DBI                  1.1.1      2021-01-15 [1] CRAN (R 4.1.0)
#>  dbplyr               2.1.1      2021-04-06 [1] CRAN (R 4.1.0)
#>  dials              * 1.0.0      2022-06-14 [1] CRAN (R 4.1.3)
#>  DiceDesign           1.9        2021-02-13 [1] CRAN (R 4.1.0)
#>  digest               0.6.27     2020-10-24 [1] CRAN (R 4.1.0)
#>  dplyr              * 1.0.9      2022-04-28 [1] CRAN (R 4.1.3)
#>  ellipsis             0.3.2      2021-04-29 [1] CRAN (R 4.1.0)
#>  evaluate             0.14       2019-05-28 [1] CRAN (R 4.1.0)
#>  fansi                0.4.2      2021-01-15 [1] CRAN (R 4.1.0)
#>  fastmap              1.1.0      2021-01-25 [1] CRAN (R 4.1.0)
#>  forcats            * 0.5.1      2021-01-27 [1] CRAN (R 4.1.0)
#>  foreach              1.5.1      2020-10-15 [1] CRAN (R 4.1.0)
#>  forecast           * 8.14       2021-03-11 [1] CRAN (R 4.1.0)
#>  fracdiff             1.5-1      2020-01-24 [1] CRAN (R 4.1.0)
#>  fs                   1.5.0      2020-07-31 [1] CRAN (R 4.1.0)
#>  furrr                0.2.2      2021-01-29 [1] CRAN (R 4.1.0)
#>  future               1.21.0     2020-12-10 [1] CRAN (R 4.1.0)
#>  generics             0.1.3      2022-07-05 [1] CRAN (R 4.1.3)
#>  ggplot2            * 3.3.6      2022-05-03 [1] CRAN (R 4.1.3)
#>  globals              0.14.0     2020-11-22 [1] CRAN (R 4.1.0)
#>  glue                 1.6.2      2022-02-24 [1] CRAN (R 4.1.3)
#>  gower                0.2.2      2020-06-23 [1] CRAN (R 4.1.0)
#>  GPfit                1.0-8      2019-02-08 [1] CRAN (R 4.1.0)
#>  gtable               0.3.0      2019-03-25 [1] CRAN (R 4.1.0)
#>  hardhat              1.2.0      2022-06-30 [1] CRAN (R 4.1.3)
#>  haven                2.4.1      2021-04-23 [1] CRAN (R 4.1.0)
#>  highr                0.9        2021-04-16 [1] CRAN (R 4.1.0)
#>  hms                  1.1.0      2021-05-17 [1] CRAN (R 4.1.0)
#>  htmltools            0.5.2      2021-08-25 [1] CRAN (R 4.1.3)
#>  httr                 1.4.2      2020-07-20 [1] CRAN (R 4.1.0)
#>  infer              * 1.0.2      2022-06-10 [1] CRAN (R 4.1.3)
#>  ipred                0.9-13     2022-06-02 [1] CRAN (R 4.1.3)
#>  iterators            1.0.13     2020-10-15 [1] CRAN (R 4.1.0)
#>  janitor              2.1.0      2021-01-05 [1] CRAN (R 4.1.0)
#>  jsonlite             1.7.2      2020-12-09 [1] CRAN (R 4.1.0)
#>  knitr                1.33       2021-04-24 [1] CRAN (R 4.1.0)
#>  lattice              0.20-44    2021-05-02 [2] CRAN (R 4.1.0)
#>  lava                 1.6.9      2021-03-11 [1] CRAN (R 4.1.0)
#>  lhs                  1.1.1      2020-10-05 [1] CRAN (R 4.1.0)
#>  lifecycle            1.0.1      2021-09-24 [1] CRAN (R 4.1.3)
#>  listenv              0.8.0      2019-12-05 [1] CRAN (R 4.1.0)
#>  lmtest               0.9-38     2020-09-09 [1] CRAN (R 4.1.0)
#>  lubridate            1.8.0      2021-10-07 [1] CRAN (R 4.1.3)
#>  magrittr             2.0.1      2020-11-17 [1] CRAN (R 4.1.0)
#>  MASS                 7.3-54     2021-05-03 [2] CRAN (R 4.1.0)
#>  Matrix               1.3-3      2021-05-04 [2] CRAN (R 4.1.0)
#>  modeldata          * 1.0.0      2022-07-01 [1] CRAN (R 4.1.3)
#>  modelr               0.1.8      2020-05-19 [1] CRAN (R 4.1.0)
#>  modeltime          * 1.2.2.9000 2022-08-09 [1] local
#>  modeltime.resample * 0.2.0      2021-03-14 [1] CRAN (R 4.1.0)
#>  munsell              0.5.0      2018-06-12 [1] CRAN (R 4.1.0)
#>  nlme                 3.1-152    2021-02-04 [2] CRAN (R 4.1.0)
#>  nnet                 7.3-16     2021-05-03 [2] CRAN (R 4.1.0)
#>  parallelly           1.25.0     2021-04-30 [1] CRAN (R 4.1.0)
#>  parsnip            * 1.0.0      2022-06-16 [1] CRAN (R 4.1.3)
#>  pillar               1.8.0      2022-07-18 [1] CRAN (R 4.1.3)
#>  pkgconfig            2.0.3      2019-09-22 [1] CRAN (R 4.1.0)
#>  prettyunits          1.1.1      2020-01-24 [1] CRAN (R 4.1.0)
#>  prodlim              2019.11.13 2019-11-17 [1] CRAN (R 4.1.0)
#>  purrr              * 0.3.4      2020-04-17 [1] CRAN (R 4.1.0)
#>  quadprog             1.5-8      2019-11-20 [1] CRAN (R 4.1.0)
#>  quantmod             0.4.18     2020-12-09 [1] CRAN (R 4.1.0)
#>  R6                   2.5.0      2020-10-28 [1] CRAN (R 4.1.0)
#>  Rcpp                 1.0.7      2021-07-07 [1] CRAN (R 4.1.0)
#>  readr              * 1.4.0      2020-10-05 [1] CRAN (R 4.1.0)
#>  readxl               1.3.1      2019-03-13 [1] CRAN (R 4.1.0)
#>  recipes            * 1.0.1      2022-07-07 [1] CRAN (R 4.1.3)
#>  reprex               2.0.1      2021-08-05 [1] CRAN (R 4.1.3)
#>  rlang                1.0.4      2022-07-12 [1] CRAN (R 4.1.3)
#>  rmarkdown            2.8        2021-05-07 [1] CRAN (R 4.1.0)
#>  rpart                4.1-15     2019-04-12 [2] CRAN (R 4.1.0)
#>  rsample            * 1.0.0      2022-06-24 [1] CRAN (R 4.1.3)
#>  rstudioapi           0.13       2020-11-12 [1] CRAN (R 4.1.0)
#>  rvest                1.0.0      2021-03-09 [1] CRAN (R 4.1.0)
#>  scales             * 1.1.1      2020-05-11 [1] CRAN (R 4.1.0)
#>  sessioninfo          1.2.2      2021-12-06 [1] CRAN (R 4.1.3)
#>  snakecase            0.11.0     2019-05-25 [1] CRAN (R 4.1.0)
#>  stringi              1.6.2      2021-05-17 [1] CRAN (R 4.1.0)
#>  stringr            * 1.4.0      2019-02-10 [1] CRAN (R 4.1.0)
#>  styler               1.5.1      2021-07-13 [1] CRAN (R 4.1.0)
#>  survival             3.2-11     2021-04-26 [2] CRAN (R 4.1.0)
#>  tibble             * 3.1.8      2022-07-22 [1] CRAN (R 4.1.3)
#>  tidymodels         * 1.0.0      2022-07-13 [1] CRAN (R 4.1.3)
#>  tidyr              * 1.2.0      2022-02-01 [1] CRAN (R 4.1.3)
#>  tidyselect           1.1.2      2022-02-21 [1] CRAN (R 4.1.3)
#>  tidyverse          * 1.3.1      2021-04-15 [1] CRAN (R 4.1.0)
#>  timeDate             3043.102   2018-02-21 [1] CRAN (R 4.1.0)
#>  timetk             * 2.8.1      2022-05-31 [1] CRAN (R 4.1.3)
#>  tseries              0.10-48    2020-12-04 [1] CRAN (R 4.1.0)
#>  TTR                  0.24.2     2020-09-01 [1] CRAN (R 4.1.0)
#>  tune               * 1.0.0      2022-07-07 [1] CRAN (R 4.1.3)
#>  urca                 1.3-0      2016-09-06 [1] CRAN (R 4.1.0)
#>  utf8                 1.2.1      2021-03-12 [1] CRAN (R 4.1.0)
#>  vctrs                0.4.1      2022-04-13 [1] CRAN (R 4.1.3)
#>  withr                2.4.2      2021-04-18 [1] CRAN (R 4.1.0)
#>  workflows          * 1.0.0      2022-07-05 [1] CRAN (R 4.1.3)
#>  workflowsets       * 1.0.0      2022-07-12 [1] CRAN (R 4.1.3)
#>  xfun                 0.23       2021-05-15 [1] CRAN (R 4.1.0)
#>  xml2                 1.3.2      2020-04-23 [1] CRAN (R 4.1.0)
#>  xts                  0.12.1     2020-09-09 [1] CRAN (R 4.1.0)
#>  yaml                 2.2.1      2020-02-01 [1] CRAN (R 4.1.0)
#>  yardstick          * 1.0.0      2022-06-06 [1] CRAN (R 4.1.3)
#>  zoo                  1.8-9      2021-03-09 [1] CRAN (R 4.1.0)
#> 
#>  [1] C:/Users/Usuario/Documents/R/win-library/4.1
#>  [2] C:/Program Files/R/R-4.1.0/library
#> 
#> ------------------------------------------------------------------------------
AlbertoAlmuinha added a commit to AlbertoAlmuinha/modeltime that referenced this issue Aug 9, 2022
@AlbertoAlmuinha
update engine specific args all models - Related business-science#195
afc9a81
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