Take data from the hai_kmeans_mapped_tbl() and unnest it into a
tibble for inspection and for use in the hai_kmeans_scree_plt() function.
Arguments
- .data
You must have a tibble in the working environment from the
hai_kmeans_mapped_tbl()
Details
Takes in a single parameter of .data from hai_kmeans_mapped_tbl() and
transforms it into a tibble that is used for hai_kmeans_scree_plt(). It will
show the values (tot.withinss) at each center.
See also
Other Kmeans:
hai_kmeans_automl_predict(),
hai_kmeans_automl(),
hai_kmeans_mapped_tbl(),
hai_kmeans_obj(),
hai_kmeans_scree_plt(),
hai_kmeans_tidy_tbl(),
hai_kmeans_user_item_tbl()
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
)
kmm_tbl <- hai_kmeans_mapped_tbl(ui_tbl)
hai_kmeans_scree_data_tbl(kmm_tbl)
#> # A tibble: 15 × 2
#> centers tot.withinss
#> <int> <dbl>
#> 1 1 1.41
#> 2 2 0.592
#> 3 3 0.372
#> 4 4 0.276
#> 5 5 0.202
#> 6 6 0.159
#> 7 7 0.124
#> 8 8 0.0884
#> 9 9 0.0716
#> 10 10 0.0578
#> 11 11 0.0460
#> 12 12 0.0363
#> 13 13 0.0272
#> 14 14 0.0251
#> 15 15 0.0160