add partykit wrappers

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 0.2.1.9000
+Version: 0.2.1.9001
 Authors@R: c(
     person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre")),
     person("Davis", "Vaughan", , "[email protected]", role = "aut"),

NAMESPACE

@@ -171,13 +171,15 @@ export(bag_tree)
 export(bart)
 export(bartMachine_interval_calc)
 export(boost_tree)
+export(cforest_train)
 export(check_empty_ellipse)
 export(check_final_param)
 export(check_model_doesnt_exist)
 export(check_model_exists)
 export(contr_one_hot)
 export(control_parsnip)
 export(convert_stan_interval)
+export(ctree_train)
 export(cubist_rules)
 export(dbart_predict_calc)
 export(decision_tree)

NEWS.md

@@ -1,5 +1,7 @@
 # parsnip (development version)
 
+* Added `ctree_train()` and `cforest_train()` wrappers for the functions in the partykit package. Engines for these will be added to other parsnip extension packages.  
+
 * Exported `xgb_predict()` which wraps xgboost's `predict()` method for use with parsnip extension packages (#688).
 
 

R/partykit.R

@@ -0,0 +1,126 @@
+#' A wrapper function for conditional inference tree models
+#'
+#' These functions are slightly different APIs for [partykit::ctree()] and
+#' [partykit::cforest()] that have several important arguments as top-level
+#' arguments (as opposed to being specified in [partykit::ctree_control()]).
+#' @param formula A symbolic description of the model to be fit.
+#' @param data A data frame containing the variables in the model.
+#' @param teststat A character specifying the type of the test statistic to be
+#' applied.
+#' @param testtype A character specifying how to compute the distribution of
+#' the test statistic.
+#' @param mincriterion The value of the test statistic (for \code{testtype ==
+#' "Teststatistic"}), or 1 - p-value (for other values of \code{testtype}) that
+#' must be exceeded in order to implement a split.
+#' @param minsplit The minimum sum of weights in a node in order to be
+#' considered for splitting.
+#' @param maxdepth maximum depth of the tree. The default \code{maxdepth = Inf}
+#' means that no restrictions are applied to tree sizes.
+#' @param mtry Number of input variables randomly sampled as candidates at each
+#' node for random forest like algorithms. The default \code{mtry = Inf} means
+#' that no random selection takes place.
+#' @param ntree Number of trees to grow in a forest.
+#' @param ... Other options to pass to [partykit::ctree()] or [partykit::cforest()].
+#' @return An object of class `party` (for `ctree`) or `cforest`.
+#' @examples
+#' if (rlang::is_installed(c("modeldata", "partykit"))) {
+#'   data(bivariate, package = "modeldata")
+#'   ctree_train(Class ~ ., data = bivariate_train)
+#'   ctree_train(Class ~ ., data = bivariate_train, maxdepth = 1)
+#' }
+#' @export
+ctree_train <-
+  function(formula,
+           data,
+           minsplit = 20L,
+           maxdepth = Inf,
+           teststat = "quadratic",
+           testtype = "Bonferroni",
+           mincriterion = 0.95,
+           ...) {
+    rlang::check_installed("partykit")
+    opts <- rlang::list2(...)
+
+    if (any(names(opts) == "control")) {
+      opts$control$minsplit <- minsplit
+      opts$control$maxdepth <- maxdepth
+      opts$control$teststat <- teststat
+      opts$control$testtype <- testtype
+      opts$control$mincriterion <- mincriterion
+    } else {
+      opts$control <-
+        rlang::call2(
+          "ctree_control",
+          .ns = "partykit",
+          !!!list(
+            minsplit = minsplit,
+            maxdepth = maxdepth,
+            teststat = teststat,
+            testtype = testtype,
+            mincriterion = mincriterion
+          )
+        )
+    }
+
+    tree_call <-
+      rlang::call2(
+        "ctree",
+        .ns = "partykit",
+        formula = rlang::expr(formula),
+        data = rlang::expr(data),
+        !!!opts
+      )
+    rlang::eval_tidy(tree_call)
+  }
+
+#' @rdname ctree_train
+#' @export
+cforest_train <-
+  function(formula,
+           data,
+           minsplit = 20L,
+           maxdepth = Inf,
+           teststat = "quadratic",
+           testtype = "Univariate",
+           mincriterion = 0,
+           mtry = ceiling(sqrt(ncol(data) - 1)),
+           ntree = 500L,
+           ...) {
+    rlang::check_installed("partykit")
+    force(mtry)
+    opts <- rlang::list2(...)
+
+    if (any(names(opts) == "control")) {
+      opts$control$minsplit <- minsplit
+      opts$control$maxdepth <- maxdepth
+      opts$control$teststat <- teststat
+      opts$control$testtype <- testtype
+      opts$control$logmincriterion <- log(mincriterion)
+      opts$control$mincriterion <- mincriterion
+    } else {
+      opts$control <-
+        rlang::call2(
+          "ctree_control",
+          .ns = "partykit",
+          !!!list(
+            minsplit = minsplit,
+            maxdepth = maxdepth,
+            teststat = teststat,
+            testtype = testtype,
+            mincriterion = mincriterion,
+            saveinfo = FALSE
+          )
+        )
+    }
+    opts$mtry <- mtry
+    opts$ntree <- ntree
+    forest_call <-
+      rlang::call2(
+        "cforest",
+        .ns = "partykit",
+        formula = rlang::expr(formula),
+        data = rlang::expr(data),
+        !!!opts
+      )
+    rlang::eval_tidy(forest_call)
+  }

_pkgdown.yml

@@ -87,6 +87,7 @@ reference:
       - tidy.model_fit
       - translate
       - starts_with("update")
+      - matches("_train")
 
   - title: Developer tools
     contents: