descriptors with fit_xy #208
Description
library(tidymodels)
#> ── Attaching packages ─────────────────────────────────────────────────────────────────────── tidymodels 0.0.2 ──
#> ✔ broom 0.5.2 ✔ purrr 0.3.2
#> ✔ dials 0.0.2.9001 ✔ recipes 0.1.6.9000
#> ✔ dplyr 0.8.3 ✔ rsample 0.0.5
#> ✔ ggplot2 3.2.1 ✔ tibble 2.1.3
#> ✔ infer 0.4.0.1 ✔ yardstick 0.0.3.9000
#> ✔ parsnip 0.0.3.9000
#> ── Conflicts ────────────────────────────────────────────────────────────────────────── tidymodels_conflicts() ──
#> ✖ purrr::discard() masks scales::discard()
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag() masks stats::lag()
#> ✖ ggplot2::margin() masks dials::margin()
#> ✖ dials::offset() masks stats::offset()
#> ✖ recipes::step() masks stats::step()
boost_tree(mode = "regression", mtry = 3) %>%
set_engine("xgboost") %>%
fit_xy(x = mtcars[, -1], y = mtcars$mpg)
#> parsnip model object
#>
#> ##### xgb.Booster
#> raw: 11.2 Kb
#> call:
#> xgboost::xgb.train(params = list(eta = 0.3, max_depth = 6, gamma = 0,
#> colsample_bytree = 0.3, min_child_weight = 1, subsample = 1),
#> data = x, nrounds = 15, verbose = 0, objective = "reg:linear",
#> nthread = 1)
#> params (as set within xgb.train):
#> eta = "0.3", max_depth = "6", gamma = "0", colsample_bytree = "0.3", min_child_weight = "1", subsample = "1", objective = "reg:linear", nthread = "1", silent = "1"
#> xgb.attributes:
#> niter
#> # of features: 10
#> niter: 15
#> nfeatures : 10
boost_tree(mode = "regression", mtry = .cols()) %>%
set_engine("xgboost") %>%
fit_xy(x = mtcars[, -1], y = mtcars$mpg)
#> Error in terms.formula(formula, data = data): argument is not a valid modelCreated on 2019-08-29 by the reprex package (v0.2.1)
The issue is that the descriptor generator uses get_descr_form() instead of get_descr_xy()