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document censored regression as a possible mode (#1040)
* use @inheritParams nearest_neighbor rather then boost_tree * add possible values for censored regression
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R/bag_tree.R

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

R/bart.R

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

R/boost_tree.R

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

R/c5_rules.R

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

R/cubist_rules.R

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

R/discrim_flexible.R

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

R/discrim_linear.R

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

R/discrim_quad.R

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

R/discrim_regularized.R

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

R/gen_additive_mod.R

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

R/mars.R

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

R/mlp.R

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

R/naive_Bayes.R

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

R/nearest_neighbor.R

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

R/pls.R

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

R/poisson_reg.R

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

R/proportional_hazards.R

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

R/rule_fit.R

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

R/surv_reg.R

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

R/survival_reg.R

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

R/svm_linear.R

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

R/svm_poly.R

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

R/svm_rbf.R

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

man/bag_tree.Rd

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man/boost_tree.Rd

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man/decision_tree.Rd

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man/rand_forest.Rd

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