summary_mc_cv: Summary for max_coverage cross validation

In njtierney/maxcovr: A Set of Tools For Solving The Maximal Covering Location Problem

Summary for max_coverage cross validation

Description

Summary for max_coverage cross validation

Usage

summary_mc_cv(model, test_data)

Arguments

model	the cross validated model.
test_data	the cross validated test data.

Value

a summary dataframe

Examples

## Not run: 

library(tidyverse)

york_selected <- york |> filter(grade == "I")
york_unselected <- york |> filter(grade != "I")

mc_cv_fixed <- modelr::crossv_kfold(york_crime, 5) |>
                 mutate(test = map(test,as_tibble),
                 train = map(train,as_tibble))

mc_cv_fit <- map_df(mc_cv_fixed$train,
                    ~max_coverage(existing_facility = york_selected,
                    proposed_facility = york_unselected,
                    user = .,
                    n_added = 20,
                    distance_cutoff = 100))

 summary_mc_cv(mc_cv_fit,
               mc_cv_fixed$test)


## End(Not run)

njtierney/maxcovr documentation built on Nov. 27, 2024, 7:51 a.m.