hai_kmeans_tidy_tbl {healthyR.ai} | R Documentation |
K-Means Object Tidy Functions
Description
K-Means tidy functions
Usage
hai_kmeans_tidy_tbl(.kmeans_obj, .data, .tidy_type = "tidy")
kmeans_tidy_tbl(.kmeans_obj, .data, .tidy_type = "tidy")
Arguments
.kmeans_obj |
A |
.data |
The user item tibble created from |
.tidy_type |
"tidy","glance", or "augment" |
Details
Takes in a k-means object and its associated user item tibble and then
returns one of the items asked for. Either: broom::tidy()
, broom::glance()
or broom::augment()
. The function defaults to broom::tidy()
.
Value
A tibble
Author(s)
Steven P. Sanderson II, MPH
See Also
Other Kmeans:
hai_kmeans_automl()
,
hai_kmeans_automl_predict()
,
hai_kmeans_mapped_tbl()
,
hai_kmeans_obj()
,
hai_kmeans_scree_data_tbl()
,
hai_kmeans_scree_plt()
,
hai_kmeans_user_item_tbl()
Examples
library(healthyR.data)
library(dplyr)
library(broom)
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()
uit_tbl <- hai_kmeans_user_item_tbl(
.data = data_tbl,
.row_input = service_line,
.col_input = payer_grouping,
.record_input = record
)
km_obj <- hai_kmeans_obj(uit_tbl)
hai_kmeans_tidy_tbl(
.kmeans_obj = km_obj,
.data = uit_tbl,
.tidy_type = "augment"
)
hai_kmeans_tidy_tbl(
.kmeans_obj = km_obj,
.data = uit_tbl,
.tidy_type = "glance"
)
hai_kmeans_tidy_tbl(
.kmeans_obj = km_obj,
.data = uit_tbl,
.tidy_type = "tidy"
) %>%
glimpse()
[Package healthyR.ai version 0.1.1 Index]