SubgroupAuditorFitter {mcboost} | R Documentation |
Static AuditorFitter based on Subgroups
Description
Used to assess multi-calibration based on a list of
binary subgroup_masks
passed during initialization.
Value
list
with items
-
corr
: pseudo-correlation between residuals and learner prediction. -
l
: the trained learner.
Super class
mcboost::AuditorFitter
-> SubgroupAuditorFitter
Public fields
subgroup_masks
list
List of subgroup masks. Initialize a SubgroupAuditorFitter
Methods
Public methods
Inherited methods
Method new()
Initializes a SubgroupAuditorFitter
that
assesses multi-calibration within each group defined
by the ‘subpops’.
Usage
SubgroupAuditorFitter$new(subgroup_masks)
Arguments
subgroup_masks
list
List of subgroup masks. Subgroup masks are list(s) of integer masks, each with the same length as data to be fitted on. They allow defining subgroups of the data.
Method fit()
Fit the learner and compute correlation
Usage
SubgroupAuditorFitter$fit(data, resid, mask)
Arguments
data
data.table
Features.resid
numeric
Residuals (of same length as data).mask
integer
Mask applied to the data. Only used forSubgroupAuditorFitter
.
Method clone()
The objects of this class are cloneable with this method.
Usage
SubgroupAuditorFitter$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
See Also
Other AuditorFitter:
CVLearnerAuditorFitter
,
LearnerAuditorFitter
,
SubpopAuditorFitter
Examples
library("data.table")
data = data.table(
"AGE_0_10" = c(1, 1, 0, 0, 0),
"AGE_11_20" = c(0, 0, 1, 0, 0),
"AGE_21_31" = c(0, 0, 0, 1, 1),
"X1" = runif(5),
"X2" = runif(5)
)
label = c(1,0,0,1,1)
masks = list(
"M1" = c(1L, 0L, 1L, 1L, 0L),
"M2" = c(1L, 0L, 0L, 0L, 1L)
)
sg = SubgroupAuditorFitter$new(masks)