tests/testthat/_snaps/svm_linear.md

In tidymodels/parsnip: A Common API to Modeling and Analysis Functions

updating

Code
  svm_linear(mode = "regression", cost = 2) %>% set_engine("kernlab", cross = 10) %>%
    update(cross = tune(), cost = tune())
Output
  Linear Support Vector Machine Model Specification (regression)

  Main Arguments:
    cost = tune()

  Engine-Specific Arguments:
    cross = tune()

  Computational engine: kernlab

bad input

Code
  translate(svm_linear(mode = "regression") %>% set_engine(NULL))
Condition
  Error in `set_engine()`:
  ! Missing engine. Possible mode/engine combinations are: classification {LiblineaR, kernlab} and regression {LiblineaR, kernlab}.

Code
  svm_linear(mode = "reallyunknown")
Condition
  Error in `svm_linear()`:
  ! "reallyunknown" is not a known mode for model `svm_linear()`.

Code
  translate(svm_linear(mode = "regression") %>% set_engine("LiblineaR", type = 3))
Condition
  Error in `translate()`:
  ! The LiblineaR engine argument `type = 3` does not correspond to an SVM regression model.

Code
  translate(svm_linear(mode = "classification") %>% set_engine("LiblineaR", type = 11))
Condition
  Error in `translate()`:
  ! The LiblineaR engine argument of `type = 11` does not correspond to an SVM classification model.

linear svm classification prediction: LiblineaR

Code
  predict(cls_form, hpc_no_m[ind, -5], type = "prob")
Condition
  Error in `predict()`:
  ! No "prob" prediction method available for this model. `type` should be one of: "class" and "raw".

Code
  predict(cls_xy_form, hpc_no_m[ind, -5], type = "prob")
Condition
  Error in `predict()`:
  ! No "prob" prediction method available for this model. `type` should be one of: "class" and "raw".

tidymodels/parsnip documentation built on Feb. 19, 2025, 2:10 a.m.