Comments (7)
simonpcouch
commented on August 10, 2024
1
Looks like they were present in the original issue tidymodels/tune#697 which gives us a slightly more minimal reprex:
library(tidymodels)
val_split <- initial_validation_split(mtcars)
val_set <- validation_set(val_split)
# fit_resamples() and tune_*() work with rsets
res <- fit_resamples(linear_reg(), mpg ~ ., resamples = val_set)
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercionCreated on 2023-09-28 with reprex v2.0.2
from rsample.
hfrick
commented on August 10, 2024
1
Thanks for finding this! So validation_set (as opposed to validation_split) needs its own pretty() method. That should go into rsample so I'm moving the issue there.
from rsample.
simonpcouch
commented on August 10, 2024
I attempted to transition to the new interface in this test but saw new warnings from [.tbl_df:
library(tidymodels)
data(ames, package = "modeldata")
mod <- parsnip::decision_tree(cost_complexity = tune()) %>%
parsnip::set_mode("regression")
set.seed(1)
three_way_split <- rsample::initial_validation_split(ames, prop = c(.8, .1))
folds <- rsample::validation_set(three_way_split)
set.seed(1)
res <-
mod %>%
tune_bayes(
Sale_Price ~ Neighborhood + Gr_Liv_Area + Year_Built + Bldg_Type +
Latitude + Longitude,
resamples = folds,
initial = 3,
metrics = yardstick::metric_set(rsq),
param_info = parameters(dials::cost_complexity(c(-2, 0)))
)
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> → A | warning: A correlation computation is required, but `estimate` is constant and has 0 standard deviation, resulting in a divide by 0 error. `NA` will be returned.
#> ! For the rsq estimates, 1 missing value was found and removed before fitting
#> the Gaussian process model.
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> ! For the rsq estimates, 2 missing values were found and removed before
#> fitting the Gaussian process model.
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> ! For the rsq estimates, 3 missing values were found and removed before
#> fitting the Gaussian process model.
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> ! For the rsq estimates, 4 missing values were found and removed before
#> fitting the Gaussian process model.
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> ! For the rsq estimates, 5 missing values were found and removed before
#> fitting the Gaussian process model.
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> ! For the rsq estimates, 6 missing values were found and removed before
#> fitting the Gaussian process model.
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> There were issues with some computations A: x7
#> Created on 2023-09-27 with reprex v2.0.2
Reprex with old interface
library(tidymodels)
data(ames, package = "modeldata")
mod <- parsnip::decision_tree(cost_complexity = tune()) %>%
parsnip::set_mode("regression")
set.seed(1)
folds <- rsample::validation_split(ames, .9)
#> Warning: `validation_split()` was deprecated in rsample 1.2.0.
#> ℹ Please use `initial_validation_split()` instead.
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
#> generated.
set.seed(1)
res <-
mod %>%
tune_bayes(
Sale_Price ~ Neighborhood + Gr_Liv_Area + Year_Built + Bldg_Type +
Latitude + Longitude,
resamples = folds,
initial = 3,
metrics = yardstick::metric_set(rsq),
param_info = parameters(dials::cost_complexity(c(-2, 0)))
)
#> → A | warning: A correlation computation is required, but `estimate` is constant and has 0 standard deviation, resulting in a divide by 0 error. `NA` will be returned.
#> ! For the rsq estimates, 1 missing value was found and removed before fitting
#> the Gaussian process model.
#> ! For the rsq estimates, 2 missing values were found and removed before
#> fitting the Gaussian process model.
#> ! For the rsq estimates, 3 missing values were found and removed before
#> fitting the Gaussian process model.
#> ! For the rsq estimates, 4 missing values were found and removed before
#> fitting the Gaussian process model.
#> ! For the rsq estimates, 5 missing values were found and removed before
#> fitting the Gaussian process model.
#> ! For the rsq estimates, 6 missing values were found and removed before
#> fitting the Gaussian process model.
#> ! For the rsq estimates, 7 missing values were found and removed before
#> fitting the Gaussian process model.
#> There were issues with some computations A: x8
#> Created on 2023-09-27 with reprex v2.0.2
Is this behavior expected? cc @hfrick—I think I may have missed that these were new in tidymodels/tune#697.
from rsample.
hfrick
commented on August 10, 2024
hm no, this is not expected. I also don't see that warning with my versions installed. which versions are you using?
(I also don't get that warning with the dev version of tune.)
─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.3.1 (2023-06-16)
os macOS Ventura 13.5.2
system aarch64, darwin20
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz Europe/London
date 2023-09-28
pandoc NA
─ Packages ───────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
backports 1.4.1 2021-12-13 [1] CRAN (R 4.3.0)
broom * 1.0.5 2023-06-09 [1] CRAN (R 4.3.0)
cachem 1.0.8 2023-05-01 [1] CRAN (R 4.3.1)
callr 3.7.3 2022-11-02 [1] CRAN (R 4.3.0)
class 7.3-22 2023-05-03 [2] CRAN (R 4.3.1)
cli 3.6.1.9000 2023-09-26 [1] Github (r-lib/cli@641fe8c)
codetools 0.2-19 2023-02-01 [2] CRAN (R 4.3.1)
colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.3.0)
crayon 1.5.2 2022-09-29 [1] CRAN (R 4.3.0)
data.table 1.14.8 2023-02-17 [1] CRAN (R 4.3.1)
devtools * 2.4.4 2022-07-20 [1] CRAN (R 4.3.0)
dials * 1.2.0 2023-04-03 [1] CRAN (R 4.3.1)
DiceDesign 1.9 2021-02-13 [1] CRAN (R 4.3.0)
digest 0.6.33 2023-07-07 [1] CRAN (R 4.3.1)
dplyr * 1.1.2 2023-04-20 [1] CRAN (R 4.3.0)
ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.3.0)
fansi 1.0.4 2023-01-22 [1] CRAN (R 4.3.0)
fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.3.1)
foreach 1.5.2 2022-02-02 [1] CRAN (R 4.3.0)
fs 1.6.3 2023-07-20 [1] CRAN (R 4.3.1)
furrr 0.3.1 2022-08-15 [1] CRAN (R 4.3.1)
future 1.33.0 2023-07-01 [1] CRAN (R 4.3.1)
future.apply 1.11.0 2023-05-21 [1] CRAN (R 4.3.1)
generics 0.1.3 2022-07-05 [1] CRAN (R 4.3.0)
ggplot2 * 3.4.3 2023-08-14 [1] CRAN (R 4.3.0)
globals 0.16.2 2022-11-21 [1] CRAN (R 4.3.0)
glue 1.6.2 2022-02-24 [1] CRAN (R 4.3.0)
gower 1.0.1 2022-12-22 [1] CRAN (R 4.3.1)
GPfit 1.0-8 2019-02-08 [1] CRAN (R 4.3.0)
gtable 0.3.3 2023-03-21 [1] CRAN (R 4.3.1)
hardhat 1.3.0 2023-03-30 [1] CRAN (R 4.3.0)
htmltools 0.5.6 2023-08-10 [1] CRAN (R 4.3.0)
htmlwidgets 1.6.2 2023-03-17 [1] CRAN (R 4.3.0)
httpuv 1.6.11 2023-05-11 [1] CRAN (R 4.3.0)
infer * 1.0.4 2022-12-02 [1] CRAN (R 4.3.1)
ipred 0.9-14 2023-03-09 [1] CRAN (R 4.3.1)
iterators 1.0.14 2022-02-05 [1] CRAN (R 4.3.0)
later 1.3.1 2023-05-02 [1] CRAN (R 4.3.0)
lattice 0.21-8 2023-04-05 [2] CRAN (R 4.3.1)
lava 1.7.2.1 2023-02-27 [1] CRAN (R 4.3.1)
lhs 1.1.6 2022-12-17 [1] CRAN (R 4.3.1)
lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.3.0)
listenv 0.9.0 2022-12-16 [1] CRAN (R 4.3.1)
lubridate 1.9.2 2023-02-10 [1] CRAN (R 4.3.1)
magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.0)
MASS 7.3-60 2023-05-04 [2] CRAN (R 4.3.1)
Matrix 1.6-1 2023-08-14 [1] CRAN (R 4.3.0)
memoise 2.0.1 2021-11-26 [1] CRAN (R 4.3.0)
mime 0.12 2021-09-28 [1] CRAN (R 4.3.0)
miniUI 0.1.1.1 2018-05-18 [1] CRAN (R 4.3.0)
modeldata * 1.2.0 2023-08-09 [1] CRAN (R 4.3.0)
modelenv 0.1.1 2023-03-08 [1] CRAN (R 4.3.1)
munsell 0.5.0 2018-06-12 [1] CRAN (R 4.3.0)
nnet 7.3-19 2023-05-03 [2] CRAN (R 4.3.1)
parallelly 1.36.0 2023-05-26 [1] CRAN (R 4.3.1)
parsnip * 1.1.1 2023-08-17 [1] CRAN (R 4.3.1)
pillar 1.9.0 2023-03-22 [1] CRAN (R 4.3.0)
pkgbuild 1.3.1 2021-12-20 [1] CRAN (R 4.3.0)
pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.0)
pkgload 1.3.2.1 2023-07-08 [1] CRAN (R 4.3.1)
prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.3.0)
processx 3.8.2 2023-06-30 [1] CRAN (R 4.3.1)
prodlim 2023.03.31 2023-04-02 [1] CRAN (R 4.3.1)
profvis 0.3.7 2020-11-02 [1] CRAN (R 4.3.0)
promises 1.2.1 2023-08-10 [1] CRAN (R 4.3.0)
prompt 1.0.1 2021-03-12 [1] CRAN (R 4.3.0)
ps 1.7.5 2023-04-18 [1] CRAN (R 4.3.1)
purrr * 1.0.2 2023-08-10 [1] CRAN (R 4.3.0)
R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.0)
Rcpp 1.0.11 2023-07-06 [1] CRAN (R 4.3.1)
recipes * 1.0.7 2023-08-10 [1] CRAN (R 4.3.0)
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rlang 1.1.1.9000 2023-09-26 [1] Github (r-lib/rlang@c55f602)
rpart * 4.1.19 2022-10-21 [2] CRAN (R 4.3.1)
rsample * 1.2.0 2023-08-23 [1] CRAN (R 4.3.1)
rstudioapi 0.15.0 2023-07-07 [1] CRAN (R 4.3.1)
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sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.3.0)
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stringi 1.7.12 2023-01-11 [1] CRAN (R 4.3.0)
stringr 1.5.0 2022-12-02 [1] CRAN (R 4.3.0)
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timechange 0.2.0 2023-01-11 [1] CRAN (R 4.3.1)
timeDate 4022.108 2023-01-07 [1] CRAN (R 4.3.1)
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xtable 1.8-4 2019-04-21 [1] CRAN (R 4.3.0)
yardstick * 1.2.0 2023-04-21 [1] CRAN (R 4.3.0)
from rsample.
simonpcouch
commented on August 10, 2024
Hmm, they look very similar. My dplyr is one version off from yours but I was able to downgrade and still see those warnings.
library(tidymodels)
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.3.1 (2023-06-16)
#> os macOS Ventura 13.5.2
#> system aarch64, darwin20
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/Chicago
#> date 2023-09-28
#> pandoc 3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> backports 1.4.1 2021-12-13 [1] CRAN (R 4.3.0)
#> broom * 1.0.5 2023-06-09 [1] CRAN (R 4.3.0)
#> class 7.3-22 2023-05-03 [2] CRAN (R 4.3.1)
#> cli 3.6.1 2023-03-23 [1] CRAN (R 4.3.0)
#> codetools 0.2-19 2023-02-01 [2] CRAN (R 4.3.1)
#> colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.3.0)
#> data.table 1.14.8 2023-02-17 [1] CRAN (R 4.3.0)
#> dials * 1.2.0 2023-04-03 [1] CRAN (R 4.3.0)
#> DiceDesign 1.9 2021-02-13 [1] CRAN (R 4.3.0)
#> digest 0.6.33 2023-07-07 [1] CRAN (R 4.3.0)
#> dplyr * 1.1.3 2023-09-03 [1] CRAN (R 4.3.0)
#> evaluate 0.21 2023-05-05 [1] CRAN (R 4.3.0)
#> fansi 1.0.4 2023-01-22 [1] CRAN (R 4.3.0)
#> fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.3.0)
#> foreach 1.5.2 2022-02-02 [1] CRAN (R 4.3.0)
#> fs 1.6.3 2023-07-20 [1] CRAN (R 4.3.0)
#> furrr 0.3.1 2022-08-15 [1] CRAN (R 4.3.0)
#> future 1.33.0 2023-07-01 [1] CRAN (R 4.3.0)
#> future.apply 1.11.0 2023-05-21 [1] CRAN (R 4.3.0)
#> generics 0.1.3 2022-07-05 [1] CRAN (R 4.3.0)
#> ggplot2 * 3.4.3 2023-08-14 [1] CRAN (R 4.3.0)
#> globals 0.16.2 2022-11-21 [1] CRAN (R 4.3.0)
#> glue 1.6.2 2022-02-24 [1] CRAN (R 4.3.0)
#> gower 1.0.1 2022-12-22 [1] CRAN (R 4.3.0)
#> GPfit 1.0-8 2019-02-08 [1] CRAN (R 4.3.0)
#> gtable 0.3.4 2023-08-21 [1] CRAN (R 4.3.0)
#> hardhat 1.3.0 2023-03-30 [1] CRAN (R 4.3.0)
#> htmltools 0.5.6 2023-08-10 [1] CRAN (R 4.3.0)
#> infer * 1.0.5 2023-09-06 [1] CRAN (R 4.3.0)
#> ipred 0.9-14 2023-03-09 [1] CRAN (R 4.3.0)
#> iterators 1.0.14 2022-02-05 [1] CRAN (R 4.3.0)
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#> lava 1.7.2.1 2023-02-27 [1] CRAN (R 4.3.0)
#> lhs 1.1.6 2022-12-17 [1] CRAN (R 4.3.0)
#> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.3.0)
#> listenv 0.9.0 2022-12-16 [1] CRAN (R 4.3.0)
#> lubridate 1.9.2 2023-02-10 [1] CRAN (R 4.3.0)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.0)
#> MASS 7.3-60 2023-05-04 [2] CRAN (R 4.3.1)
#> Matrix 1.6-1.1 2023-09-18 [1] CRAN (R 4.3.1)
#> modeldata * 1.2.0 2023-08-09 [1] CRAN (R 4.3.0)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.3.0)
#> nnet 7.3-19 2023-05-03 [2] CRAN (R 4.3.1)
#> parallelly 1.36.0 2023-05-26 [1] CRAN (R 4.3.0)
#> parsnip * 1.1.1 2023-08-17 [1] CRAN (R 4.3.0)
#> pillar 1.9.0 2023-03-22 [1] CRAN (R 4.3.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.0)
#> prodlim 2023.08.28 2023-08-28 [1] CRAN (R 4.3.0)
#> purrr * 1.0.2 2023-08-10 [1] CRAN (R 4.3.0)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.0)
#> Rcpp 1.0.11 2023-07-06 [1] CRAN (R 4.3.0)
#> recipes * 1.0.8 2023-08-25 [1] CRAN (R 4.3.0)
#> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.3.0)
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#> vctrs 0.6.3 2023-06-14 [1] CRAN (R 4.3.0)
#> withr 2.5.0 2022-03-03 [1] CRAN (R 4.3.0)
#> workflows * 1.1.3 2023-02-22 [1] CRAN (R 4.3.0)
#> workflowsets * 1.0.1 2023-04-06 [1] CRAN (R 4.3.0)
#> xfun 0.40 2023-08-09 [1] CRAN (R 4.3.0)
#> yaml 2.3.7 2023-01-23 [1] CRAN (R 4.3.0)
#> yardstick * 1.2.0 2023-04-21 [1] CRAN (R 4.3.0)
#>
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#> [2] /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library
#>
#> ──────────────────────────────────────────────────────────────────────────────Created on 2023-09-28 with reprex v2.0.2
from rsample.
simonpcouch
commented on August 10, 2024
Ah, okay. tune::pull_rset_attributes() calls pretty() on the inputted resamples, giving:
library(tidymodels)
val_split <- initial_validation_split(mtcars)
val_set <- validation_set(val_split)
pretty(val_set)
#> Warning in `[.tbl_df`(x, is.finite(x <- as.numeric(x))): NAs introduced by
#> coercion
#> # A tibble: 0 × 0
# previously...
val_set_old <- validation_split(mtcars)
#> Warning: `validation_split()` was deprecated in rsample 1.2.0.
#> ℹ Please use `initial_validation_split()` instead.
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
#> generated.
pretty(val_set_old)
#> [1] "Validation Set Split (0.75/0.25) "Created on 2023-09-28 with reprex v2.0.2
from rsample.
github-actions
commented on August 10, 2024
This issue has been automatically locked. If you believe you have found a related problem, please file a new issue (with a reprex: https://reprex.tidyverse.org) and link to this issue.
from rsample.
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- Use cli errors in `R/tidy.R`, `R/validation_set.R`, `R/vfold.R`
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from rsample.