| model_info.WrappedModel | R Documentation |
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
## S3 method for class 'WrappedModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'H2ORegressionModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'H2OBinomialModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'H2OMultinomialModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'scikitlearn_model'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'keras'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'LearnerRegr'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'LearnerClassif'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'GraphLearner'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'xgb.Booster'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'workflow'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'model_stack'
model_info(model, is_multiclass = FALSE, ...)
model |
- model object |
is_multiclass |
- if TRUE and task is classification, then multitask classification is set. Else is omitted. If |
... |
- another arguments |
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
A named list of class model_info
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