model_info.WrappedModel: Exract info from model

Description

This generic function let user extract base information about model. The function returns a named list of class model_info that contain about package of model, version and task type. For wrappers like mlr or caret both, package and wrapper information are stored

Usage

# S3 method for WrappedModel
model_info(model, is_multiclass = FALSE, ...)
# S3 method for H2ORegressionModel
model_info(model, is_multiclass = FALSE, ...)
# S3 method for H2OBinomialModel
model_info(model, is_multiclass = FALSE, ...)
# S3 method for H2OMultinomialModel
model_info(model, is_multiclass = FALSE, ...)
# S3 method for scikitlearn_model
model_info(model, is_multiclass = FALSE, ...)
# S3 method for keras
model_info(model, is_multiclass = FALSE, ...)
# S3 method for LearnerRegr
model_info(model, is_multiclass = FALSE, ...)
# S3 method for LearnerClassif
model_info(model, is_multiclass = FALSE, ...)
# S3 method for GraphLearner
model_info(model, is_multiclass = FALSE, ...)
# S3 method for xgb.Booster
model_info(model, is_multiclass = FALSE, ...)
# S3 method for workflow
model_info(model, is_multiclass = FALSE, ...)
# S3 method for model_stack
model_info(model, is_multiclass = FALSE, ...)

Value

A named list of class model_info

Arguments

model: - model object
is_multiclass: - if TRUE and task is classification, then multitask classification is set. Else is omitted. If model_info was executed withing explain function. DALEX will recognize subtype on it's own. @param is_multiclass
...: - another arguments

Details

Currently supported packages are:

mlr models created with mlr package
h2o models created with h2o package
scikit-learn models created with scikit-learn Python library and accessed via reticulate
keras models created with keras Python library and accessed via reticulate
mlr3 models created with mlr3 package
xgboost models created with xgboost package
tidymodels models created with tidymodels package