update

ML/2-modeling-reg.R

@@ -54,6 +54,8 @@ ds_test  <- ds_test %>% dplyr::select(-ft4_dia)
 data_folds <- rsamp$vfold_cv(ds_train, repeats = 5)
 
 
+pred <- dplyr::select(ds_train, -FT4, -subject_id, -charttime)
+
 # recipes ------------------------------------------------------------------
 
 
@@ -62,8 +64,9 @@ normalized_rec <- r$recipe(FT4 ~ ., data = ds_train) %>%
   r$update_role(subject_id, new_role = "id") %>%
   r$update_role(charttime, new_role = "time") %>%
   r$step_impute_bag(r$all_predictors()) %>%
-  r$step_BoxCox(r$all_numeric()) %>%
+  r$step_dummy(r$all_nominal_predictors()) %>%
   r$step_corr(r$all_numeric_predictors()) %>%
+  r$step_log(r$all_numeric()) %>%
   r$step_normalize(r$all_numeric())
 
 
@@ -99,7 +102,7 @@ rf_spec <-
 
 xgb_spec <-
   p$boost_tree(tree_depth = tune(), learn_rate = tune(), loss_reduction = tune(),
-             min_n = tune(), sample_size = tune(), trees = tune()) %>%
+               min_n = tune(), sample_size = tune(), trees = tune()) %>%
   p$set_engine("xgboost") %>%
   p$set_mode("regression")
 
@@ -111,6 +114,13 @@ nnet_param <-
   update(hidden_units = d$hidden_units(c(1, 27)))
 
 
+rf_parma <-
+  rf_spec %>%
+  tune$extract_parameter_set_dials() %>%
+  update(mtry = d$finalize(d$mtry(), pred))
+
+
+
 
 # workflows ---------------------------------------------------------------
 
@@ -131,3 +141,23 @@ forests <-
 all_workflows <-
   dplyr::bind_rows(normalized, forests) %>%
   dplyr::mutate(wflow_id = gsub("(forests_)|(normalized_)", "", wflow_id))
+
+
+
+# grid search -------------------------------------------------------------
+
+grid_ctrl <-
+  tune$control_grid(
+    save_pred = TRUE,
+    parallel_over = "everything",
+    save_workflow = TRUE
+  )
+
+grid_results <-
+  all_workflows %>%
+  workflowsets::workflow_map(
+    seed = 070823
+    ,resamples = data_folds
+    ,grid = 25
+    ,control = grid_ctrl
+  )