- name
character name of the object to which the model is assigned.
- label
optional character descriptor for the model.
- packages
character vector of package names upon which the model
depends. Each name may be optionally followed by a comment in
parentheses specifying a version requirement. The comment should contain
a comparison operator, whitespace and a valid version number, e.g.
"xgboost (>= 1.3.0)"
.
- response_types
character vector of response variable types to which
the model can be fit. Supported types are "binary"
,
"BinomialVariate"
, "DiscreteVariate"
, "factor"
,
"matrix"
, "NegBinomialVariate"
, "numeric"
,
"ordered"
, "PoissonVariate"
, and "Surv"
.
- weights
logical value or vector of the same length as
response_types
indicating whether case weights are supported for
the responses.
- predictor_encoding
character string indicating whether the model is
fit with predictor variables encoded as a "model.frame"
,
a "model.matrix"
, or unspecified (default).
- na.rm
character string or logical specifying removal of "all"
(TRUE
) cases with missing values from model fitting and prediction,
"none"
(FALSE
), or only those whose missing values are in the
"response"
variable.
- params
list of user-specified model parameters to be passed to the
fit
function.
- gridinfo
tibble of information for construction of tuning grids
consisting of a character column param
with the names of parameters
in the grid, a list column get_values
with functions to generate grid
points for the corresponding parameters, and an optional logical column
default
indicating which parameters to include by default in regular
grids. Values functions may optionally include arguments n
and
data
for the number of grid points to generate and a
ModelFrame
of the model fit data and formula, respectively;
and must include an ellipsis (...
).
- fit
model fitting function whose arguments are a formula
, a
ModelFrame
named data
, case weights
, and an
ellipsis.
- predict
model prediction function whose arguments are the
object
returned by fit
, a ModelFrame
named
newdata
of predictor variables, optional vector of times
at
which to predict survival, and an ellipsis.
- varimp
variable importance function whose arguments are the
object
returned by fit
, optional arguments passed from calls
to varimp
, and an ellipsis.
- ...
arguments passed to other methods.
- object
function that returns an MLModel
object when called
without any supplied argument values.