diff --git a/man/details_boost_tree_xgboost.Rd b/man/details_boost_tree_xgboost.Rd
index 7c220533b..bc1ba3b2d 100644
--- a/man/details_boost_tree_xgboost.Rd
+++ b/man/details_boost_tree_xgboost.Rd
@@ -26,6 +26,9 @@ below)
\item \code{stop_iter}: # Iterations Before Stopping (type: integer, default:
Inf)
}
+
+For \code{mtry}, the default value of \code{NULL} translates to using all
+available columns.
}
\subsection{Translation from parsnip to the original package (regression)}{
diff --git a/man/details_gen_additive_mod_mgcv.Rd b/man/details_gen_additive_mod_mgcv.Rd
index 1eb1b6bb9..db9f55eab 100644
--- a/man/details_gen_additive_mod_mgcv.Rd
+++ b/man/details_gen_additive_mod_mgcv.Rd
@@ -93,10 +93,9 @@ The smoothness of the terms will need to be manually specified (e.g.,
using \code{s(x, df = 10)}) in the formula. Tuning can be accomplished using
the \code{adjust_deg_free} parameter.
-However, when using a workflow, the best approach is to avoid using
-\code{\link[workflows:add_formula]{workflows::add_formula()}} and use
-\code{\link[workflows:add_variables]{workflows::add_variables()}} in
-conjunction with a model formula:
+When using a workflow, pass the \emph{model formula} to
+\code{\link[=add_model]{add_model()}}’s \code{formula} argument, and a simplified
+\emph{preprocessing formula} elsewhere.
\if{html}{\out{}}\preformatted{spec <-
gen_additive_mod() \%>\%
@@ -104,8 +103,8 @@ conjunction with a model formula:
set_mode("regression")
workflow() \%>\%
- add_variables(outcomes = c(mpg), predictors = c(wt, gear, cyl, disp)) \%>\%
add_model(spec, formula = mpg ~ wt + gear + cyl + s(disp, k = 10)) \%>\%
+ add_formula(mpg ~ wt + gear + cyl + disp) \%>\%
fit(data = mtcars) \%>\%
extract_fit_engine()
}\if{html}{\out{
}}
@@ -123,9 +122,8 @@ workflow() \%>\%
## GCV score: 4.225228
}\if{html}{\out{}}
-The reason for this is that
-\code{\link[workflows:add_formula]{workflows::add_formula()}} will try to
-create the model matrix and fail to find/use \code{s()}.
+To learn more about the differences between these formulas, see
+\code{\link[=model_formula]{?model_formula}}.
}
\subsection{Preprocessing requirements}{
diff --git a/man/details_mlp_brulee.Rd b/man/details_mlp_brulee.Rd
index 775d831c2..bac98abc6 100644
--- a/man/details_mlp_brulee.Rd
+++ b/man/details_mlp_brulee.Rd
@@ -15,9 +15,9 @@ This model has 7 tuning parameters:
\item \code{hidden_units}: # Hidden Units (type: integer, default: 3L)
\item \code{penalty}: Amount of Regularization (type: double, default: 0.0)
\item \code{mixture}: Proportion of Lasso Penalty (type: double, default: 0.0)
-\item \code{epochs}: # Epochs (type: integer, default: 0.01)
+\item \code{epochs}: # Epochs (type: integer, default: 100L)
\item \code{dropout}: Dropout Rate (type: double, default: 0.0)
-\item \code{learn_rate}: Learning Rate (type: double, default: 100L)
+\item \code{learn_rate}: Learning Rate (type: double, default: 0.01)
\item \code{activation}: Activation Function (type: character, default: ‘relu’)
}
diff --git a/man/details_proportional_hazards_glmnet.Rd b/man/details_proportional_hazards_glmnet.Rd
index 1e1f9e1a3..c03ff3967 100644
--- a/man/details_proportional_hazards_glmnet.Rd
+++ b/man/details_proportional_hazards_glmnet.Rd
@@ -72,9 +72,11 @@ The model does not fit an intercept.
The model formula (which is required) can include \emph{special} terms, such
as \code{\link[survival:strata]{survival::strata()}}. This allows the baseline
-hazard to differ between groups contained in the function. The column
-used inside \code{strata()} is treated as qualitative no matter its type.
-This is different than the syntax offered by the
+hazard to differ between groups contained in the function. (To learn
+more about using special terms in formulas with tidymodels, see
+\code{\link[=model_formula]{?model_formula}}.) The column used inside
+\code{strata()} is treated as qualitative no matter its type. This is
+different than the syntax offered by the
\code{\link[glmnet:glmnet]{glmnet::glmnet()}} package (i.e.,
\code{\link[glmnet:stratifySurv]{glmnet::stratifySurv()}}) which is not
recommended here.
@@ -101,10 +103,10 @@ predict(mod, pred_data, type = "survival", time = 500) \%>\%
}\if{html}{\out{}}
\if{html}{\out{}}\preformatted{## # A tibble: 2 × 5
-## .time .pred_survival age ecog.ps rx
-##
-## 1 500 0.666 50 1 1
-## 2 500 0.769 50 1 2
+## .eval_time .pred_survival age ecog.ps rx
+##
+## 1 500 0.666 50 1 1
+## 2 500 0.769 50 1 2
}\if{html}{\out{
}}
Note that columns used in the \code{strata()} function \emph{will} also be
diff --git a/man/details_proportional_hazards_survival.Rd b/man/details_proportional_hazards_survival.Rd
index 1e6cb151f..77b655404 100644
--- a/man/details_proportional_hazards_survival.Rd
+++ b/man/details_proportional_hazards_survival.Rd
@@ -46,7 +46,9 @@ model specification typically involved the use of
The model formula can include \emph{special} terms, such as
\code{\link[survival:strata]{survival::strata()}}. The allows the baseline
hazard to differ between groups contained in the function. The column
-used inside \code{strata()} is treated as qualitative no matter its type.
+used inside \code{strata()} is treated as qualitative no matter its type. To
+learn more about using special terms in formulas with tidymodels, see
+\code{\link[=model_formula]{?model_formula}}.
For example, in this model, the numeric column \code{rx} is used to estimate
two different baseline hazards for each value of the column:
diff --git a/man/details_surv_reg_survival.Rd b/man/details_surv_reg_survival.Rd
index 91e12434d..688df2671 100644
--- a/man/details_surv_reg_survival.Rd
+++ b/man/details_surv_reg_survival.Rd
@@ -49,7 +49,9 @@ model specification typically involved the use of
The model formula can include \emph{special} terms, such as
\code{\link[survival:strata]{survival::strata()}}. The allows the model scale
parameter to differ between groups contained in the function. The column
-used inside \code{strata()} is treated as qualitative no matter its type.
+used inside \code{strata()} is treated as qualitative no matter its type. To
+learn more about using special terms in formulas with tidymodels, see
+\code{\link[=model_formula]{?model_formula}}.
For example, in this model, the numeric column \code{rx} is used to estimate
two different scale parameters for each value of the column:
diff --git a/man/details_survival_reg_survival.Rd b/man/details_survival_reg_survival.Rd
index 2b68ebf62..102575585 100644
--- a/man/details_survival_reg_survival.Rd
+++ b/man/details_survival_reg_survival.Rd
@@ -54,7 +54,9 @@ model specification typically involved the use of
The model formula can include \emph{special} terms, such as
\code{\link[survival:strata]{survival::strata()}}. The allows the model scale
parameter to differ between groups contained in the function. The column
-used inside \code{strata()} is treated as qualitative no matter its type.
+used inside \code{strata()} is treated as qualitative no matter its type. To
+learn more about using special terms in formulas with tidymodels, see
+\code{\link[=model_formula]{?model_formula}}.
For example, in this model, the numeric column \code{rx} is used to estimate
two different scale parameters for each value of the column:
diff --git a/man/rmd/gen_additive_mod_mgcv.Rmd b/man/rmd/gen_additive_mod_mgcv.Rmd
index daa5a0201..dddf85839 100644
--- a/man/rmd/gen_additive_mod_mgcv.Rmd
+++ b/man/rmd/gen_additive_mod_mgcv.Rmd
@@ -60,7 +60,7 @@ gen_additive_mod() %>%
The smoothness of the terms will need to be manually specified (e.g., using `s(x, df = 10)`) in the formula. Tuning can be accomplished using the `adjust_deg_free` parameter.
-However, when using a workflow, the best approach is to avoid using [workflows::add_formula()] and use [workflows::add_variables()] in conjunction with a model formula:
+When using a workflow, pass the _model formula_ to [add_model()]'s `formula` argument, and a simplified _preprocessing formula_ elsewhere.
```{r}
spec <-
@@ -69,13 +69,13 @@ spec <-
set_mode("regression")
workflow() %>%
- add_variables(outcomes = c(mpg), predictors = c(wt, gear, cyl, disp)) %>%
add_model(spec, formula = mpg ~ wt + gear + cyl + s(disp, k = 10)) %>%
+ add_formula(mpg ~ wt + gear + cyl + disp) %>%
fit(data = mtcars) %>%
extract_fit_engine()
```
-The reason for this is that [workflows::add_formula()] will try to create the model matrix and fail to find/use `s()`.
+To learn more about the differences between these formulas, see [`?model_formula`][parsnip::model_formula].
## Preprocessing requirements
diff --git a/man/rmd/gen_additive_mod_mgcv.md b/man/rmd/gen_additive_mod_mgcv.md
index 6727227ba..ffc84d81a 100644
--- a/man/rmd/gen_additive_mod_mgcv.md
+++ b/man/rmd/gen_additive_mod_mgcv.md
@@ -96,7 +96,7 @@ gen_additive_mod() %>%
The smoothness of the terms will need to be manually specified (e.g., using `s(x, df = 10)`) in the formula. Tuning can be accomplished using the `adjust_deg_free` parameter.
-However, when using a workflow, the best approach is to avoid using [workflows::add_formula()] and use [workflows::add_variables()] in conjunction with a model formula:
+When using a workflow, pass the _model formula_ to [add_model()]'s `formula` argument, and a simplified _preprocessing formula_ elsewhere.
```r
@@ -106,8 +106,8 @@ spec <-
set_mode("regression")
workflow() %>%
- add_variables(outcomes = c(mpg), predictors = c(wt, gear, cyl, disp)) %>%
add_model(spec, formula = mpg ~ wt + gear + cyl + s(disp, k = 10)) %>%
+ add_formula(mpg ~ wt + gear + cyl + disp) %>%
fit(data = mtcars) %>%
extract_fit_engine()
```
@@ -126,7 +126,7 @@ workflow() %>%
## GCV score: 4.225228
```
-The reason for this is that [workflows::add_formula()] will try to create the model matrix and fail to find/use `s()`.
+To learn more about the differences between these formulas, see [`?model_formula`][parsnip::model_formula].
## Preprocessing requirements
diff --git a/man/rmd/glmnet-details.md b/man/rmd/glmnet-details.md
index 2a1147a9a..ed6c119d2 100644
--- a/man/rmd/glmnet-details.md
+++ b/man/rmd/glmnet-details.md
@@ -169,7 +169,7 @@ tidy(fit)
## 4 hp -0.0101 1
## 5 drat 0 1
## 6 wt -2.59 1
-## # … with 5 more rows
+## # ℹ 5 more rows
```
Note that there is a `tidy()` method for `glmnet` objects in the `broom` package. If this is used directly on the underlying `glmnet` object, it returns _all of coefficients on the path_:
@@ -191,7 +191,7 @@ all_tidy_coefs
## 4 (Intercept) 4 24.7 3.89 0.347
## 5 (Intercept) 5 26.0 3.55 0.429
## 6 (Intercept) 6 27.2 3.23 0.497
-## # … with 634 more rows
+## # ℹ 634 more rows
```
```r
diff --git a/man/rmd/proportional_hazards_glmnet.Rmd b/man/rmd/proportional_hazards_glmnet.Rmd
index ffa2cd215..b639f8a46 100644
--- a/man/rmd/proportional_hazards_glmnet.Rmd
+++ b/man/rmd/proportional_hazards_glmnet.Rmd
@@ -54,7 +54,7 @@ By default, [glmnet::glmnet()] uses the argument `standardize = TRUE` to center
The model does not fit an intercept.
-The model formula (which is required) can include _special_ terms, such as [survival::strata()]. This allows the baseline hazard to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. This is different than the syntax offered by the [glmnet::glmnet()] package (i.e., [glmnet::stratifySurv()]) which is not recommended here.
+The model formula (which is required) can include _special_ terms, such as [survival::strata()]. This allows the baseline hazard to differ between groups contained in the function. (To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].) The column used inside `strata()` is treated as qualitative no matter its type. This is different than the syntax offered by the [glmnet::glmnet()] package (i.e., [glmnet::stratifySurv()]) which is not recommended here.
For example, in this model, the numeric column `rx` is used to estimate two different baseline hazards for each value of the column:
diff --git a/man/rmd/proportional_hazards_glmnet.md b/man/rmd/proportional_hazards_glmnet.md
index bb1619f2c..c294ca1ad 100644
--- a/man/rmd/proportional_hazards_glmnet.md
+++ b/man/rmd/proportional_hazards_glmnet.md
@@ -61,7 +61,7 @@ By default, [glmnet::glmnet()] uses the argument `standardize = TRUE` to center
The model does not fit an intercept.
-The model formula (which is required) can include _special_ terms, such as [survival::strata()]. This allows the baseline hazard to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. This is different than the syntax offered by the [glmnet::glmnet()] package (i.e., [glmnet::stratifySurv()]) which is not recommended here.
+The model formula (which is required) can include _special_ terms, such as [survival::strata()]. This allows the baseline hazard to differ between groups contained in the function. (To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].) The column used inside `strata()` is treated as qualitative no matter its type. This is different than the syntax offered by the [glmnet::glmnet()] package (i.e., [glmnet::stratifySurv()]) which is not recommended here.
For example, in this model, the numeric column `rx` is used to estimate two different baseline hazards for each value of the column:
@@ -89,10 +89,10 @@ predict(mod, pred_data, type = "survival", time = 500) %>%
```
## # A tibble: 2 × 5
-## .time .pred_survival age ecog.ps rx
-##
-## 1 500 0.666 50 1 1
-## 2 500 0.769 50 1 2
+## .eval_time .pred_survival age ecog.ps rx
+##
+## 1 500 0.666 50 1 1
+## 2 500 0.769 50 1 2
```
Note that columns used in the `strata()` function _will_ also be estimated in the regular portion of the model (i.e., within the linear predictor).
diff --git a/man/rmd/proportional_hazards_survival.Rmd b/man/rmd/proportional_hazards_survival.Rmd
index 588198c27..143dc2b9f 100644
--- a/man/rmd/proportional_hazards_survival.Rmd
+++ b/man/rmd/proportional_hazards_survival.Rmd
@@ -26,7 +26,7 @@ The model does not fit an intercept.
The main interface for this model uses the formula method since the model specification typically involved the use of [survival::Surv()].
-The model formula can include _special_ terms, such as [survival::strata()]. The allows the baseline hazard to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type.
+The model formula can include _special_ terms, such as [survival::strata()]. The allows the baseline hazard to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].
For example, in this model, the numeric column `rx` is used to estimate two different baseline hazards for each value of the column:
diff --git a/man/rmd/proportional_hazards_survival.md b/man/rmd/proportional_hazards_survival.md
index 3681c4920..f50970545 100644
--- a/man/rmd/proportional_hazards_survival.md
+++ b/man/rmd/proportional_hazards_survival.md
@@ -37,7 +37,7 @@ The model does not fit an intercept.
The main interface for this model uses the formula method since the model specification typically involved the use of [survival::Surv()].
-The model formula can include _special_ terms, such as [survival::strata()]. The allows the baseline hazard to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type.
+The model formula can include _special_ terms, such as [survival::strata()]. The allows the baseline hazard to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].
For example, in this model, the numeric column `rx` is used to estimate two different baseline hazards for each value of the column:
diff --git a/man/rmd/surv_reg_survival.Rmd b/man/rmd/surv_reg_survival.Rmd
index bb54fe980..fbdb24708 100644
--- a/man/rmd/surv_reg_survival.Rmd
+++ b/man/rmd/surv_reg_survival.Rmd
@@ -38,7 +38,7 @@ Note that `model = TRUE` is needed to produce quantile predictions when there is
The main interface for this model uses the formula method since the model specification typically involved the use of [survival::Surv()].
-The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type.
+The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].
For example, in this model, the numeric column `rx` is used to estimate two different scale parameters for each value of the column:
diff --git a/man/rmd/surv_reg_survival.md b/man/rmd/surv_reg_survival.md
index 8189f95dd..56e7e7765 100644
--- a/man/rmd/surv_reg_survival.md
+++ b/man/rmd/surv_reg_survival.md
@@ -40,7 +40,7 @@ Note that `model = TRUE` is needed to produce quantile predictions when there is
The main interface for this model uses the formula method since the model specification typically involved the use of [survival::Surv()].
-The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type.
+The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].
For example, in this model, the numeric column `rx` is used to estimate two different scale parameters for each value of the column:
diff --git a/man/rmd/survival_reg_survival.Rmd b/man/rmd/survival_reg_survival.Rmd
index c1b7ff855..dcaec4d92 100644
--- a/man/rmd/survival_reg_survival.Rmd
+++ b/man/rmd/survival_reg_survival.Rmd
@@ -42,7 +42,7 @@ In the translated syntax above, note that `model = TRUE` is needed to produce qu
The main interface for this model uses the formula method since the model specification typically involved the use of [survival::Surv()].
-The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type.
+The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].
For example, in this model, the numeric column `rx` is used to estimate two different scale parameters for each value of the column:
diff --git a/man/rmd/survival_reg_survival.md b/man/rmd/survival_reg_survival.md
index 0552e0eff..bbd45bcec 100644
--- a/man/rmd/survival_reg_survival.md
+++ b/man/rmd/survival_reg_survival.md
@@ -44,7 +44,7 @@ In the translated syntax above, note that `model = TRUE` is needed to produce qu
The main interface for this model uses the formula method since the model specification typically involved the use of [survival::Surv()].
-The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type.
+The model formula can include _special_ terms, such as [survival::strata()]. The allows the model scale parameter to differ between groups contained in the function. The column used inside `strata()` is treated as qualitative no matter its type. To learn more about using special terms in formulas with tidymodels, see [`?model_formula`][parsnip::model_formula].
For example, in this model, the numeric column `rx` is used to estimate two different scale parameters for each value of the column: