SelectedModel: Selected Model

In brian-j-smith/MachineShop: Machine Learning Models and Tools

Selected Model

Description

Model selection from a candidate set.

Usage

SelectedModel(...)

## Default S3 method:
SelectedModel(
  ...,
  control = MachineShop::settings("control"),
  metrics = NULL,
  cutoff = MachineShop::settings("cutoff"),
  stat = MachineShop::settings("stat.TrainingParams")
)

## S3 method for class 'ModelSpecification'
SelectedModel(
  ...,
  control = MachineShop::settings("control"),
  metrics = NULL,
  cutoff = MachineShop::settings("cutoff"),
  stat = MachineShop::settings("stat.TrainingParams")
)

## S3 method for class 'list'
SelectedModel(x, ...)

Arguments

...	model functions, function names, objects; other objects that can be coerced to models; vectors of these to serve as the candidate set from which to select, such as that returned by expand_model; or model specifications.
control	control function, function name, or object defining the resampling method to be employed.
metrics	metric function, function name, or vector of these with which to calculate performance. If not specified, default metrics defined in the performance functions are used. Model selection is based on the first calculated metric.
cutoff	argument passed to the metrics functions.
stat	function or character string naming a function to compute a summary statistic on resampled metric values for model selection.
x	list of models followed by arguments passed to their method function.

Details

Response types:

factor, numeric, ordered, Surv

Value

SelectedModel or SelectedModelSpecification class object that inherits from MLModel or ModelSpecification, respectively.

See Also

fit, resample

Examples

## Requires prior installation of suggested package gbm and glmnet to run

model_fit <- fit(
  sale_amount ~ ., data = ICHomes,
  model = SelectedModel(GBMModel, GLMNetModel, SVMRadialModel)
)
(selected_model <- as.MLModel(model_fit))
summary(selected_model)

brian-j-smith/MachineShop documentation built on Sept. 22, 2023, 10:01 p.m.