knitr::convert_chunk_header(type = "yaml")

Author: topepo

man/rmd/C5_rules_C5.0.Rmd

@@ -1,11 +1,15 @@
-```{r, child = "aaa.Rmd", include = FALSE}
+```{r}
+#| child: aaa.Rmd
+#| include: false
 ```
 
 `r descr_models("C5_rules", "C5.0")`
 
 ## Tuning Parameters
 
-```{r C5.0-param-info, echo = FALSE}
+```{r}
+#| label: C5.0-param-info
+#| echo: false
 defaults <- 
   tibble::tibble(parsnip = c("trees", "min_n"),
                  default = c("1L",       "2L"))
@@ -18,7 +22,10 @@ param <-
 
 This model has `r nrow(param)` tuning parameters:
 
-```{r C5.0-param-list, echo = FALSE, results = "asis"}
+```{r}
+#| label: C5.0-param-list
+#| echo: false
+#| results: asis
 param$item
 ```
 
@@ -28,7 +35,8 @@ Note that C5.0 has a tool for _early stopping_ during boosting where less iterat
 
 `r uses_extension("C5_rules", "C5.0", "classification")`
 
-```{r C5.0-cls}
+```{r}
+#| label: C5.0-cls
 library(rules)
 
 C5_rules(
@@ -42,17 +50,20 @@ C5_rules(
 
 ## Preprocessing requirements
 
-```{r child = "template-tree-split-factors.Rmd"}
+```{r}
+#| child: template-tree-split-factors.Rmd
 ```
 
 ## Case weights
 
-```{r child = "template-uses-case-weights.Rmd"}
+```{r}
+#| child: template-uses-case-weights.Rmd
 ```
 
 ## Saving fitted model objects
 
-```{r child = "template-butcher.Rmd"}
+```{r}
+#| child: template-butcher.Rmd
 ```
 
 

man/rmd/aaa.Rmd

@@ -1,4 +1,5 @@
-```{r, include = FALSE}
+```{r}
+#| include: false
 # pillar/cli options to try to lock down formatting
 options(useFancyQuotes = FALSE)
 options(dplyr.print_min = 6, dplyr.print_max = 6)

man/rmd/auto_ml_h2o.Rmd

@@ -1,4 +1,6 @@
-```{r, child = "aaa.Rmd", include = FALSE}
+```{r}
+#| child: aaa.Rmd
+#| include: false
 ```
 
 `r descr_models("auto_ml", "h2o")`
@@ -19,7 +21,8 @@ Engine arguments of interest
 
 [agua::h2o_train_auto()] is a wrapper around [h2o::h2o.automl()]. 
 
-```{r h2o-reg}
+```{r}
+#| label: h2o-reg
 auto_ml() |>  
   set_engine("h2o") |> 
   set_mode("regression") |> 
@@ -29,7 +32,8 @@ auto_ml() |>
 
 ## Translation from parsnip to the original package (classification)
 
-```{r h2o-cls}
+```{r}
+#| label: h2o-cls
 auto_ml() |>  
   set_engine("h2o") |> 
   set_mode("classification") |> 
@@ -38,15 +42,18 @@ auto_ml() |>
 
 ## Preprocessing requirements
 
-```{r child = "template-makes-dummies.Rmd"}
+```{r}
+#| child: template-makes-dummies.Rmd
 ```
 
 ## Initializing h2o 
 
-```{r child = "template-h2o-init.Rmd"}
+```{r}
+#| child: template-h2o-init.Rmd
 ```
 
 ## Saving fitted model objects
 
-```{r child = "template-bundle.Rmd"}
+```{r}
+#| child: template-bundle.Rmd
 ```

man/rmd/bag_mars_earth.Rmd

@@ -1,11 +1,15 @@
-```{r, child = "aaa.Rmd", include = FALSE}
+```{r}
+#| child: aaa.Rmd
+#| include: false
 ```
 
 `r descr_models("bag_mars", "earth")`
 
 ## Tuning Parameters
 
-```{r earth-param-info, echo = FALSE}
+```{r}
+#| label: earth-param-info
+#| echo: false
 defaults <- 
   tibble::tibble(parsnip = c("num_terms", "prod_degree", "prune_method"),
                  default = c("see below", "1L", "'backward'"))
@@ -18,7 +22,10 @@ param <-
 
 This model has `r nrow(param)` tuning parameters:
 
-```{r earth-param-list, echo = FALSE, results = "asis"}
+```{r}
+#| label: earth-param-list
+#| echo: false
+#| results: asis
 param$item
 ```
 
@@ -28,7 +35,8 @@ The default value of `num_terms` depends on the number of predictor columns. For
 
 `r uses_extension("bag_mars", "earth", "regression")`
 
-```{r earth-reg}
+```{r}
+#| label: earth-reg
 bag_mars(num_terms = integer(1), prod_degree = integer(1), prune_method = character(1)) |> 
   set_engine("earth") |> 
   set_mode("regression") |> 
@@ -39,7 +47,8 @@ bag_mars(num_terms = integer(1), prod_degree = integer(1), prune_method = charac
 
 `r uses_extension("bag_mars", "earth", "classification")`
 
-```{r earth-cls}
+```{r}
+#| label: earth-cls
 library(baguette)
 
 bag_mars(
@@ -54,12 +63,14 @@ bag_mars(
 
 ## Preprocessing requirements
 
-```{r child = "template-makes-dummies.Rmd"}
+```{r}
+#| child: template-makes-dummies.Rmd
 ```
 
 ## Case weights
 
-```{r child = "template-uses-case-weights.Rmd"}
+```{r}
+#| child: template-uses-case-weights.Rmd
 ```
 
 Note that the `earth` package documentation has: "In the current implementation, _building models with weights can be slow_."

man/rmd/bag_mlp_nnet.Rmd

@@ -1,11 +1,15 @@
-```{r, child = "aaa.Rmd", include = FALSE}
+```{r}
+#| child: aaa.Rmd
+#| include: false
 ```
 
 `r descr_models("bag_mlp", "nnet")`
 
 ## Tuning Parameters
 
-```{r nnet-param-info, echo = FALSE}
+```{r}
+#| label: nnet-param-info
+#| echo: false
 defaults <- 
   tibble::tibble(parsnip = c("penalty", "hidden_units", "epochs"),
                  default = c("0.0", "10L", "1000L"))
@@ -19,7 +23,10 @@ param <-
 
 This model has `r nrow(param)` tuning parameters:
 
-```{r nnet-param-list, echo = FALSE, results = "asis"}
+```{r}
+#| label: nnet-param-list
+#| echo: false
+#| results: asis
 param$item
 ```
 
@@ -29,7 +36,8 @@ These defaults are set by the `baguette` package and are different than those in
 
 `r uses_extension("bag_mlp", "nnet", "classification")`
 
-```{r nnet-cls}
+```{r}
+#| label: nnet-cls
 library(baguette)
 
 bag_mlp(penalty = double(1), hidden_units = integer(1)) |> 
@@ -43,7 +51,8 @@ bag_mlp(penalty = double(1), hidden_units = integer(1)) |>
 
 `r uses_extension("bag_mlp", "nnet", "regression")`
 
-```{r nnet-reg}
+```{r}
+#| label: nnet-reg
 library(baguette)
 
 bag_mlp(penalty = double(1), hidden_units = integer(1)) |> 
@@ -55,15 +64,18 @@ bag_mlp(penalty = double(1), hidden_units = integer(1)) |>
 
 ## Preprocessing requirements
 
-```{r child = "template-makes-dummies.Rmd"}
+```{r}
+#| child: template-makes-dummies.Rmd
 ```
 
-```{r child = "template-same-scale.Rmd"}
+```{r}
+#| child: template-same-scale.Rmd
 ```
 
 ## Case weights
 
-```{r child = "template-no-case-weights.Rmd"}
+```{r}
+#| child: template-no-case-weights.Rmd
 ```
 
 

man/rmd/bag_tree_C5.0.Rmd

@@ -1,11 +1,15 @@
-```{r, child = "aaa.Rmd", include = FALSE}
+```{r}
+#| child: aaa.Rmd
+#| include: false
 ```
 
 `r descr_models("bag_tree", "C5.0")`
 
 ## Tuning Parameters
 
-```{r C5.0-param-info, echo = FALSE}
+```{r}
+#| label: C5.0-param-info
+#| echo: false
 defaults <- 
   tibble::tibble(parsnip = c("min_n"),
                  default = c("2L"))
@@ -19,15 +23,19 @@ param <-
 
 This model has `r nrow(param)` tuning parameters:
 
-```{r C5.0-param-list, echo = FALSE, results = "asis"}
+```{r}
+#| label: C5.0-param-list
+#| echo: false
+#| results: asis
 param$item
 ```
 
 ## Translation from parsnip to the original package (classification)
 
 `r uses_extension("bag_tree", "C5.0", "classification")`
 
-```{r C5.0-cls}
+```{r}
+#| label: C5.0-cls
 library(baguette)
 
 bag_tree(min_n = integer()) |> 
@@ -38,12 +46,14 @@ bag_tree(min_n = integer()) |>
 
 ## Preprocessing requirements
 
-```{r child = "template-tree-split-factors.Rmd"}
+```{r}
+#| child: template-tree-split-factors.Rmd
 ```
 
 ## Case weights
 
-```{r child = "template-uses-case-weights.Rmd"}
+```{r}
+#| child: template-uses-case-weights.Rmd
 ```