K-Means Mapping Function

Create a tibble that maps the hai_kmeans_obj() using purrr::map() to create a nested data.frame/tibble that holds n centers. This tibble will be used to help create a scree plot.

Usage

hai_kmeans_mapped_tbl(.data, .centers = 15)

kmeans_mapped_tbl(.data, .centers = 15)

Arguments

.data: You must have a tibble in the working environment from the hai_kmeans_user_item_tbl()
.centers: How many different centers do you want to try

Value

A nested tibble

Details

Takes in a single parameter of .centers. This is used to create the tibble and map the hai_kmeans_obj() function down the list creating a nested tibble.

Author

Steven P. Sanderson II, MPH

Examples

library(healthyR.data)
library(dplyr)

data_tbl <- healthyR_data %>%
  filter(ip_op_flag == "I") %>%
  filter(payer_grouping != "Medicare B") %>%
  filter(payer_grouping != "?") %>%
  select(service_line, payer_grouping) %>%
  mutate(record = 1) %>%
  as_tibble()

ui_tbl <- hai_kmeans_user_item_tbl(
  .data = data_tbl,
  .row_input = service_line,
  .col_input = payer_grouping,
  .record_input = record
)

hai_kmeans_mapped_tbl(ui_tbl)
#> # A tibble: 15 × 3
#>    centers k_means  glance          
#>      <int> <list>   <list>          
#>  1       1 <kmeans> <tibble [1 × 4]>
#>  2       2 <kmeans> <tibble [1 × 4]>
#>  3       3 <kmeans> <tibble [1 × 4]>
#>  4       4 <kmeans> <tibble [1 × 4]>
#>  5       5 <kmeans> <tibble [1 × 4]>
#>  6       6 <kmeans> <tibble [1 × 4]>
#>  7       7 <kmeans> <tibble [1 × 4]>
#>  8       8 <kmeans> <tibble [1 × 4]>
#>  9       9 <kmeans> <tibble [1 × 4]>
#> 10      10 <kmeans> <tibble [1 × 4]>
#> 11      11 <kmeans> <tibble [1 × 4]>
#> 12      12 <kmeans> <tibble [1 × 4]>
#> 13      13 <kmeans> <tibble [1 × 4]>
#> 14      14 <kmeans> <tibble [1 × 4]>
#> 15      15 <kmeans> <tibble [1 × 4]>