Nothing
Code
svm_poly()
Output
Polynomial Support Vector Machine Model Specification (unknown mode)
Computational engine: kernlab
Code
boost_tree(mtry = 5)
Output
Boosted Tree Model Specification (unknown mode)
Main Arguments:
mtry = 5
Computational engine: xgboost
Code
rand_forest() %>% set_mode("regression")
Output
Random Forest Model Specification (regression)
Computational engine: ranger
Code
logistic_reg() %>% set_engine("glmnet", penalty = 0.5)
Output
Logistic Regression Model Specification (classification)
Engine-Specific Arguments:
penalty = 0.5
Computational engine: glmnet
Code
mlp() %>% set_mode("classification") %>% translate()
Output
Single Layer Neural Network Model Specification (classification)
Main Arguments:
hidden_units = 5
Computational engine: nnet
Model fit template:
nnet::nnet(formula = missing_arg(), data = missing_arg(), size = 5,
trace = FALSE, linout = FALSE)
print_model_spec()
handles args correctlyCode
print_model_spec(linear_reg())
Output
Linear Regression Model Specification (regression)
Computational engine: lm
Code
print_model_spec(lr)
Message
! parsnip could not locate an implementation for `beep` model specifications.
Output
beep Model Specification (regression)
Computational engine: lm
Code
print_model_spec(lr, cls = "boop")
Message
! parsnip could not locate an implementation for `boop` model specifications.
Output
boop Model Specification (regression)
Computational engine: lm
Code
print_model_spec(lr, cls = "boop", desc = "Boop")
Message
! parsnip could not locate an implementation for `boop` model specifications.
Output
Boop Model Specification (regression)
Computational engine: lm
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