fit {MachineShop} | R Documentation |
Model Fitting
Description
Fit a model to estimate its parameters from a data set.
Usage
fit(...)
## S3 method for class 'formula'
fit(formula, data, model, ...)
## S3 method for class 'matrix'
fit(x, y, model, ...)
## S3 method for class 'ModelFrame'
fit(input, model, ...)
## S3 method for class 'recipe'
fit(input, model, ...)
## S3 method for class 'ModelSpecification'
fit(object, verbose = FALSE, ...)
## S3 method for class 'MLModel'
fit(model, ...)
## S3 method for class 'MLModelFunction'
fit(model, ...)
Arguments
... |
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 specification. |
verbose |
logical indicating whether to display printed output generated by some model-specific fit functions to aid in monitoring progress and diagnosing errors. |
Details
User-specified case weights may be specified for ModelFrames
upon
creation with the weights
argument in its
constructor.
Variables in recipe
specifications may be designated as case weights
with the role_case
function.
Value
MLModelFit
class object.
See Also
as.MLModel
, response
,
predict
, varimp
Examples
## Requires prior installation of suggested package gbm to run
## Survival response example
library(survival)
gbm_fit <- fit(Surv(time, status) ~ ., data = veteran, model = GBMModel)
varimp(gbm_fit)