Nothing
#' Example Analysis of Ames Housing Data
#'
#' @details
#' These objects are the results of an analysis of the Ames
#' housing data. A K-nearest neighbors model was used with a small
#' predictor set that included natural spline transformations of
#' the `Longitude` and `Latitude` predictors. The code used to
#' generate these examples was:
#'
#' ```
#' library(tidymodels)
#' library(tune)
#' library(AmesHousing)
#'
#' # ------------------------------------------------------------------------------
#'
#' ames <- make_ames()
#'
#' set.seed(4595)
#' data_split <- initial_split(ames, strata = "Sale_Price")
#'
#' ames_train <- training(data_split)
#'
#' set.seed(2453)
#' rs_splits <- vfold_cv(ames_train, strata = "Sale_Price")
#'
#' # ------------------------------------------------------------------------------
#'
#' ames_rec <-
#' recipe(Sale_Price ~ ., data = ames_train) %>%
#' step_log(Sale_Price, base = 10) %>%
#' step_YeoJohnson(Lot_Area, Gr_Liv_Area) %>%
#' step_other(Neighborhood, threshold = .1) %>%
#' step_dummy(all_nominal()) %>%
#' step_zv(all_predictors()) %>%
#' step_ns(Longitude, deg_free = tune("lon")) %>%
#' step_ns(Latitude, deg_free = tune("lat"))
#'
#' knn_model <-
#' nearest_neighbor(
#' mode = "regression",
#' neighbors = tune("K"),
#' weight_func = tune(),
#' dist_power = tune()
#' ) %>%
#' set_engine("kknn")
#'
#' ames_wflow <-
#' workflow() %>%
#' add_recipe(ames_rec) %>%
#' add_model(knn_model)
#'
#' ames_set <-
#' extract_parameter_set_dials(ames_wflow) %>%
#' update(K = neighbors(c(1, 50)))
#'
#' set.seed(7014)
#' ames_grid <-
#' ames_set %>%
#' grid_max_entropy(size = 10)
#'
#' ames_grid_search <-
#' tune_grid(
#' ames_wflow,
#' resamples = rs_splits,
#' grid = ames_grid
#' )
#'
#' set.seed(2082)
#' ames_iter_search <-
#' tune_bayes(
#' ames_wflow,
#' resamples = rs_splits,
#' param_info = ames_set,
#' initial = ames_grid_search,
#' iter = 15
#' )
#' ```
#'
#' __important note__: Since the `rsample` split columns contain a reference
#' to the same data, saving them to disk can results in large object sizes when
#' the object is later used. In essence, R replaces all of those references with
#' the actual data. For this reason, we saved zero-row tibbles in their place.
#' This doesn't affect how we use these objects in examples but be advised that
#' using some `rsample` functions on them will cause issues.
#'
#' @name example_ames_knn
#' @aliases ames_wflow ames_grid_search ames_iter_search
#' @docType data
#' @return \item{ames_wflow}{A workflow object}
#' \item{ames_grid_search,ames_iter_search}{Results of model tuning. }
#'
#'
#' @keywords datasets
#' @examples
#' library(tune)
#'
#' ames_grid_search
#' ames_iter_search
NULL
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.