model_fit | R Documentation |
An object with class "model_fit" is a container for information about a model that has been fit to the data.
The main elements of the object are:
lvl
: A vector of factor levels when the outcome is
a factor. This is NULL
when the outcome is not a factor
vector.
spec
: A model_spec
object.
fit
: The object produced by the fitting function.
preproc
: This contains any data-specific information
required to process new a sample point for prediction. For
example, if the underlying model function requires arguments x
and y
and the user passed a formula to fit
, the preproc
object would contain items such as the terms object and so on.
When no information is required, this is NA
.
As discussed in the documentation for model_spec
, the
original arguments to the specification are saved as quosures.
These are evaluated for the model_fit
object prior to fitting.
If the resulting model object prints its call, any user-defined
options are shown in the call preceded by a tilde (see the
example below). This is a result of the use of quosures in the
specification.
This class and structure is the basis for how parsnip stores model objects after seeing the data and applying a model.
# Keep the `x` matrix if the data are not too big.
spec_obj <-
linear_reg() %>%
set_engine("lm", x = ifelse(.obs() < 500, TRUE, FALSE))
spec_obj
fit_obj <- fit(spec_obj, mpg ~ ., data = mtcars)
fit_obj
nrow(fit_obj$fit$x)
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