document censored regression as a possible mode

R/bag_tree.R

@@ -10,6 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
+#' @inheritParams boost_tree
 #' @inheritParams decision_tree
 #' @param class_cost A non-negative scalar for a class cost (where a cost of 1
 #' means no extra cost). This is useful for when the first level of the outcome

R/bart.R

@@ -11,6 +11,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
+#' @inheritParams nearest_neighbor
 #' @inheritParams boost_tree
 #' @param prior_terminal_node_coef A coefficient for the prior probability that
 #' a node is a terminal node. Values are usually between 0 and one with

R/boost_tree.R

@@ -15,8 +15,8 @@
 #' \url{https://www.tidymodels.org/}.
 #'
 #' @param mode A single character string for the prediction outcome mode.
-#'  Possible values for this model are "unknown", "regression", or
-#'  "classification".
+#'  Possible values for this model are "unknown", "regression",
+#'  "classification", or "censored regression".
 #' @param engine A single character string specifying what computational engine
 #'  to use for fitting.
 #' @param mtry A number for the number (or proportion) of predictors that will

R/c5_rules.R

@@ -13,7 +13,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param mode A single character string for the type of model.
 #'  The only possible value for this model is "classification".
 #' @param trees A non-negative integer (no greater than 100) for the number

R/cubist_rules.R

@@ -10,7 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param mode A single character string for the type of model.
 #'  The only possible value for this model is "regression".
 #' @param committees A non-negative integer (no greater than 100) for the number

R/discrim_flexible.R

@@ -11,7 +11,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @inheritParams discrim_linear
 #' @param num_terms The number of features that will be retained in the
 #'    final model, including the intercept.

R/discrim_linear.R

@@ -13,7 +13,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param mode A single character string for the type of model. The only
 #'  possible value for this model is "classification".
 #' @param penalty An non-negative number representing the amount of

R/discrim_quad.R

@@ -13,7 +13,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param mode A single character string for the type of model. The only
 #'  possible value for this model is "classification".
 #' @param regularization_method A character string for the type of regularized

R/discrim_regularized.R

@@ -13,7 +13,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @inheritParams discrim_linear
 #' @param frac_common_cov,frac_identity Numeric values between zero and one.
 #'

R/gen_additive_mod.R

@@ -10,7 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param select_features `TRUE` or `FALSE.` If `TRUE`, the model has the
 #'  ability to eliminate a predictor (via penalization). Increasing
 #'  `adjust_deg_free` will increase the likelihood of removing predictors.

R/mars.R

@@ -12,7 +12,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param num_terms The number of features that will be retained in the
 #'    final model, including the intercept.
 #' @param prod_degree The highest possible interaction degree.

R/mlp.R

@@ -10,6 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
+#' @inheritParams nearest_neighbor
 #' @inheritParams boost_tree
 #' @param hidden_units An integer for the number of units in the hidden model.
 #' @param penalty A non-negative numeric value for the amount of weight

R/naive_Bayes.R

@@ -11,7 +11,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @inheritParams discrim_linear
 #' @param smoothness An non-negative number representing the the relative
 #'  smoothness of the class boundary. Smaller examples result in model flexible

R/nearest_neighbor.R

@@ -11,7 +11,11 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @param mode A single character string for the prediction outcome mode.
+#'  Possible values for this model are "unknown", "regression", or
+#'  "classification".
+#' @param engine A single character string specifying what computational engine
+#'  to use for fitting.
 #' @param neighbors A single integer for the number of neighbors
 #' to consider (often called `k`). For \pkg{kknn}, a value of 5
 #' is used if `neighbors` is not specified.

R/pls.R

@@ -10,7 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param predictor_prop The maximum proportion of original predictors that can
 #'  have _non-zero_ coefficients for each PLS component (via regularization).
 #'  This value is used for all PLS components for X.

R/poisson_reg.R

@@ -10,7 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param mode A single character string for the type of model.
 #'  The only possible value for this model is "regression".
 #' @param penalty A non-negative number representing the total

R/proportional_hazards.R

@@ -10,7 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @inheritParams linear_reg
 #' @param mode A single character string for the prediction outcome mode.
 #'  The only possible value for this model is "censored regression".

R/rule_fit.R

@@ -10,6 +10,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
+#' @inheritParams nearest_neighbor
 #' @inheritParams boost_tree
 #' @param penalty L1 regularization parameter.
 #' @details

R/surv_reg.R

@@ -11,7 +11,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param mode A single character string for the prediction outcome mode.
 #'  The only possible value for this model is "regression".
 #' @param dist A character string for the probability distribution of the

R/survival_reg.R

@@ -9,7 +9,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param mode A single character string for the prediction outcome mode.
 #'  The only possible value for this model is "censored regression".
 #' @param dist A character string for the probability distribution of the

R/svm_linear.R

@@ -13,7 +13,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param cost A positive number for the cost of predicting a sample within
 #'  or on the wrong side of the margin
 #' @param margin A positive number for the epsilon in the SVM insensitive

R/svm_poly.R

@@ -14,7 +14,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param cost A positive number for the cost of predicting a sample within
 #'  or on the wrong side of the margin
 #' @param degree A positive number for polynomial degree.

R/svm_rbf.R

@@ -14,7 +14,7 @@
 #' More information on how \pkg{parsnip} is used for modeling is at
 #' \url{https://www.tidymodels.org/}.
 #'
-#' @inheritParams boost_tree
+#' @inheritParams nearest_neighbor
 #' @param engine A single character string specifying what computational engine
 #'  to use for fitting. Possible engines are listed below. The default for this
 #'  model is `"kernlab"`.