在 tidymodels 中调整 catboost 时与标签相关的错误
Error related to labels when tuning catboost in tidymodels
这是模型:
cb_spec <- boost_tree(
mode = "classification",
trees = 1000,
tree_depth = tune(),
min_n = tune(),
mtry = tune(),
learn_rate = tune()
) %>%
set_engine("catboost", loss_function = "Logloss", task_type = "GPU")
这是食谱:
cb_rec <- recipe(covid_vaccination ~ ., data = cb_train) %>%
step_unknown(all_nominal_predictors()) %>%
#step_dummy(all_nominal_predictors(), one_hot = TRUE) %>%
step_impute_median(all_numeric_predictors()) %>%
step_nzv(all_predictors())
我把它们结合起来:
cb_wf <- workflow() %>%
add_model(cb_spec) %>%
add_recipe(cb_rec)
然后我尝试调整以找到最佳超参数:
cb_tune <- tune_grid(
object = cb_wf,
resamples = cb_folds,
grid = cb_grid,
metrics = metric_set(roc_auc),
control = control_grid(verbose = TRUE)
)
这是我得到的错误:
Error in catboost.from_matrix(as.matrix(float_and_cat_features_data),
: Unsupported label type, expecting double or integer.
我已经确认分类变量已更改为因子。我的数据集中绝对没有字符类型向量。
https://github.com/catboost/catboost/issues/1874
多亏了一个很棒的人,他自己制作了 treesnip 的分支作为解决方法:Mikhail Rudakov
这是模型:
cb_spec <- boost_tree(
mode = "classification",
trees = 1000,
tree_depth = tune(),
min_n = tune(),
mtry = tune(),
learn_rate = tune()
) %>%
set_engine("catboost", loss_function = "Logloss", task_type = "GPU")
这是食谱:
cb_rec <- recipe(covid_vaccination ~ ., data = cb_train) %>%
step_unknown(all_nominal_predictors()) %>%
#step_dummy(all_nominal_predictors(), one_hot = TRUE) %>%
step_impute_median(all_numeric_predictors()) %>%
step_nzv(all_predictors())
我把它们结合起来:
cb_wf <- workflow() %>%
add_model(cb_spec) %>%
add_recipe(cb_rec)
然后我尝试调整以找到最佳超参数:
cb_tune <- tune_grid(
object = cb_wf,
resamples = cb_folds,
grid = cb_grid,
metrics = metric_set(roc_auc),
control = control_grid(verbose = TRUE)
)
这是我得到的错误:
Error in catboost.from_matrix(as.matrix(float_and_cat_features_data), : Unsupported label type, expecting double or integer.
我已经确认分类变量已更改为因子。我的数据集中绝对没有字符类型向量。
https://github.com/catboost/catboost/issues/1874
多亏了一个很棒的人,他自己制作了 treesnip 的分支作为解决方法:Mikhail Rudakov