resample | R Documentation |
Estimation of the predictive performance of a model estimated and evaluated on training and test samples generated from an observed data set.
resample(...)
## S3 method for class 'formula'
resample(formula, data, model, ...)
## S3 method for class 'matrix'
resample(x, y, model, ...)
## S3 method for class 'ModelFrame'
resample(input, model, ...)
## S3 method for class 'recipe'
resample(input, model, ...)
## S3 method for class 'ModelSpecification'
resample(object, control = MachineShop::settings("control"), ...)
## S3 method for class 'MLModel'
resample(model, ...)
## S3 method for class 'MLModelFunction'
resample(model, ...)
... |
arguments passed from the generic function to its methods, from
the |
formula , data |
formula defining the model predictor and response variables and a data frame containing them. |
model |
model function, function name, or object; or another object that can be coerced to a model. A model can be given first followed by any of the variable specifications. |
x , y |
matrix and object containing predictor and response variables. |
input |
input object defining and containing the model predictor and response variables. |
object |
model input or specification. |
control |
control function, function name, or object defining the resampling method to be employed. |
Stratified resampling is performed automatically for the formula
and
matrix
methods according to the type of response variable. In
general, strata are constructed from numeric proportions for
BinomialVariate
; original values for character
,
factor
, logical
, and ordered
; first columns of values
for matrix
; original values for numeric
; and numeric times
within event statuses for Surv
. Numeric values are stratified into
quantile bins and categorical values into factor levels defined by
MLControl
.
Resampling stratification variables may be specified manually for
ModelFrames
upon creation with the strata
argument in their constructor. Resampling of this class is unstratified by
default.
Stratification variables may be designated in recipe
specifications
with the role_case
function. Resampling will be unstratified
otherwise.
Resample
class object.
c
, metrics
, performance
,
plot
, summary
## Requires prior installation of suggested package gbm to run
## Factor response example
fo <- Species ~ .
control <- CVControl()
gbm_res1 <- resample(fo, iris, GBMModel(n.trees = 25), control)
gbm_res2 <- resample(fo, iris, GBMModel(n.trees = 50), control)
gbm_res3 <- resample(fo, iris, GBMModel(n.trees = 100), control)
summary(gbm_res1)
plot(gbm_res1)
res <- c(GBM1 = gbm_res1, GBM2 = gbm_res2, GBM3 = gbm_res3)
summary(res)
plot(res)
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