tests/testthat/_snaps/model-catboost.md

In tidypredict: Run Predictions Inside the Database

unsupported objective throws error

Code
  tidypredict_fit(pm)
Condition
  Error in `build_fit_formula_catboost_nested()`:
  ! Unsupported objective: "UnsupportedObjective".
  i Supported objectives: "RMSE", "MAE", "Quantile", "MAPE", "Poisson", "Huber", "LogCosh", "Expectile", "Tweedie", "Logloss", "CrossEntropy", "MultiClass", and "MultiClassOneVsAll".

empty trees throws error

Code
  tidypredict_fit(pm)
Condition
  Error in `build_fit_formula_catboost_nested()`:
  ! Model has no trees.

tidypredict_test requires matrix

Code
  tidypredict_test(model)
Condition
  Error in `catboost_model()`:
  ! CatBoost models require a matrix for predictions.
  i Pass the prediction matrix via the `xg_df` argument.

.extract_catboost_trees errors on non-catboost model

Code
  .extract_catboost_trees(lm(mpg ~ wt, data = mtcars))
Condition
  Error in `.extract_catboost_trees()`:
  ! `model` must be <catboost.Model>, not a <lm> object.

multiclass model requires num_class >= 2

Code
  tidypredict_fit(pm)
Condition
  Error in `build_fit_formula_catboost_multiclass_nested()`:
  ! Multiclass model must have num_class >= 2.

set_catboost_categories validates parsed_model argument

Code
  set_catboost_categories("not a parsed model", model, data.frame())
Condition
  Error in `set_catboost_categories()`:
  ! `parsed_model` must be a parsed CatBoost model.

set_catboost_categories validates model argument

Code
  set_catboost_categories(pm, "not a model", data.frame())
Condition
  Error in `set_catboost_categories()`:
  ! `model` must be a <catboost.Model>, not a string.

set_catboost_categories errors when column not found in data

Code
  set_catboost_categories(pm, model, wrong_data)
Condition
  Error in `set_catboost_categories()`:
  ! Column "cat_feat" not found in `data`.

set_catboost_categories errors when column is not a factor

Code
  set_catboost_categories(pm, model, wrong_data)
Condition
  Error in `set_catboost_categories()`:
  ! Column "cat_feat" must be a factor.

categorical features without mapping throws error

Code
  tidypredict_fit(pm)
Condition
  Error in `map()`:
  i In index: 1.
  Caused by error in `build_nested_catboost_categorical()`:
  ! No category mapping found for hash -254607792.
  i For raw CatBoost models, use `set_catboost_categories()`.

parsnip model without xlevels throws error

Code
  tidypredict_fit(model_fit)
Condition
  Error in `setup_catboost_parsnip_categories()`:
  ! Model has categorical features but no factor level information.
  i Ensure the model was fit with factor columns, not character columns.

tidypredict documentation built on Aug. 24, 2026, 9:10 a.m.