9
9
# ' @param probabilities The names of class probability estimates (if any). For
10
10
# ' classification, these should be given in the order of the factor levels of
11
11
# ' the `estimate`.
12
- # ' @param time The name of the predicted event time. (not yet supported)
13
12
# ' @examples
14
13
# '
15
14
# ' tailor()
16
15
# ' @export
17
16
tailor <- function (type = " unknown" , outcome = NULL , estimate = NULL ,
18
- probabilities = NULL , time = NULL ) {
17
+ probabilities = NULL ) {
19
18
columns <-
20
19
list (
21
20
outcome = outcome ,
22
21
type = type ,
23
22
estimate = estimate ,
24
- probabilities = probabilities ,
25
- time = time
23
+ probabilities = probabilities
26
24
)
27
25
28
26
new_tailor(
@@ -80,7 +78,7 @@ print.tailor <- function(x, ...) {
80
78
81
79
# ' @export
82
80
fit.tailor <- function (object , .data , outcome , estimate , probabilities = c(),
83
- time = c(), ... ) {
81
+ ... ) {
84
82
# ------------------------------------------------------------------------------
85
83
# set columns via tidyselect
86
84
@@ -95,13 +93,6 @@ fit.tailor <- function(object, .data, outcome, estimate, probabilities = c(),
95
93
check_selection(enquo(probabilities ), columns $ probabilities , " probabilities" )
96
94
}
97
95
98
- time <- tidyselect :: eval_select(enquo(time ), .data )
99
- if (length(time ) > 0 ) {
100
- columns $ time <- names(time )
101
- } else {
102
- columns $ time <- character (0 )
103
- }
104
-
105
96
.data <- .data [, names(.data ) %in% unlist(columns )]
106
97
if (! tibble :: is_tibble(.data )) {
107
98
.data <- tibble :: as_tibble(.data )
0 commit comments