Fitted workflows, parsnip objects, and recipes objects can be turned into an orbital object that contain all the information needed to perform predictions.
Details
An orbital object contains all the information that is needed to perform predictions. This makes the objects substantially smaller than the original objects. The main downside with this object is that all the input checking has been removed, and it is thus up to the user to make sure the data is correct.
The printing of orbital objects reduce the number of significant digits for
easy viewing, the can be changes by using the digits argument of print()
like so print(orbital_object, digits = 10). The printing likewise truncates
each equation to fit on one line. This can be turned off using the truncate
argument like so print(orbital_object, truncate = FALSE).
Full list of supported models and recipes steps can be found here:
vignette("supported-models").
These objects will not be useful by themselves. They can be used to
predict() with, or to generate code using functions
such as orbital_sql() or orbital_dt().
Examples
library(workflows)
library(recipes)
#> Loading required package: dplyr
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
#>
#> Attaching package: ‘recipes’
#> The following object is masked from ‘package:stats’:
#>
#> step
library(parsnip)
rec_spec <- recipe(mpg ~ ., data = mtcars) %>%
step_normalize(all_numeric_predictors())
lm_spec <- linear_reg()
wf_spec <- workflow(rec_spec, lm_spec)
wf_fit <- fit(wf_spec, mtcars)
orbital(wf_fit)
#>
#> ── orbital Object ────────────────────────────────────────────────────────
#> • cyl = (cyl - 6.1875) / 1.785922
#> • disp = (disp - 230.7219) / 123.9387
#> • hp = (hp - 146.6875) / 68.56287
#> • drat = (drat - 3.596562) / 0.5346787
#> • wt = (wt - 3.21725) / 0.9784574
#> • qsec = (qsec - 17.84875) / 1.786943
#> • vs = (vs - 0.4375) / 0.5040161
#> • am = (am - 0.40625) / 0.4989909
#> • gear = (gear - 3.6875) / 0.7378041
#> • carb = (carb - 2.8125) / 1.6152
#> • .pred = 20.09062 + (cyl * -0.199024) + (disp * 1.652752) + (hp * ...
#> ──────────────────────────────────────────────────────────────────────────
#> 11 equations in total.
# Also works on parsnip object by itself
fit(lm_spec, mpg ~ disp, data = mtcars) %>%
orbital()
#>
#> ── orbital Object ────────────────────────────────────────────────────────
#> • .pred = 29.59985 + (disp * -0.04121512)
#> ──────────────────────────────────────────────────────────────────────────
#> 1 equations in total.
# And prepped recipes
prep(rec_spec) %>%
orbital()
#>
#> ── orbital Object ────────────────────────────────────────────────────────
#> • cyl = (cyl - 6.1875) / 1.785922
#> • disp = (disp - 230.7219) / 123.9387
#> • hp = (hp - 146.6875) / 68.56287
#> • drat = (drat - 3.596562) / 0.5346787
#> • wt = (wt - 3.21725) / 0.9784574
#> • qsec = (qsec - 17.84875) / 1.786943
#> • vs = (vs - 0.4375) / 0.5040161
#> • am = (am - 0.40625) / 0.4989909
#> • gear = (gear - 3.6875) / 0.7378041
#> • carb = (carb - 2.8125) / 1.6152
#> ──────────────────────────────────────────────────────────────────────────
#> 10 equations in total.