model_info function

Exract info from model

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 inforamtion are stored

model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'lm'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'randomForest'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'svm'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'glm'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'lrm'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'glmnet'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'cv.glmnet'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'ranger'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'gbm'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'model_fit'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'train'
model_info(model, is_multiclass = FALSE, ...)

## S3 method for class 'rpart'
model_info(model, is_multiclass = FALSE, ...)

## Default S3 method:
model_info(model, is_multiclass = FALSE, ...)

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.

• ...: - another arguments

Returns

A named list of class model_info

Details

Currently supported packages are:

• class cv.glmnet and glmnet - models created with glmnet package
• class glm - generalized linear models
• class lrm - models created with rms package,
• class model_fit - models created with parsnip package
• class lm - linear models created with stats::lm
• class ranger - models created with ranger package
• class randomForest - random forest models created with randomForest package
• class svm - support vector machines models created with the e1071 package
• class train - models created with caret package
• class gbm - models created with gbm package

Examples

aps_lm_model4 <- lm(m2.price ~., data = apartments)
model_info(aps_lm_model4)

library("ranger")
model_regr_rf <- ranger::ranger(status~., data = HR, num.trees = 50, probability = TRUE)
model_info(model_regr_rf, is_multiclass = TRUE)