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modelling/save_dalex_rush_yards.R

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+library(dpylr)
+library(DALEXtra)
+library(here)
+library(tidymodels)
+
+setwd(here())
+
+rush_yards_tidymodel <- readRDS("./modelling/fit_rush_yards.RDS")
+
+preprocessed <- ffopportunity::ep_preprocess(nflreadr::load_pbp(2006:2021))
+
+debug(DALEXtra::explain_tidymodels)
+rush_yards_explainer <-
+  DALEXtra::explain_tidymodels(
+    rush_yards_tidymodel,
+    data = dplyr::select(preprocessed$rush_df, -rushing_yards),
+    y =  preprocessed$rush_df$rushing_yards)
+
+plot(feature_importance(rush_yards_explainer))
+
+pdp_time <-
+  model_profile(
+    rush_yards_explainer,
+    variables = "rusher_age",
+    groups = "position"
+  )
+
+plot(pdp_time)
+
+
+# testing xgb dalex -------------------------------------------------------
+
+.load_model_objs <- function(variable, version) {
+
+  cache_dir <- rappdirs::user_cache_dir("ffopportunity", "ffverse")
+
+  folder_path <- file.path(cache_dir,version)
+
+  model_path <- file.path(folder_path, paste0(variable,".xgb"))
+  blueprint_path <- file.path(folder_path, paste0(variable,".rds"))
+
+  stopifnot(file.exists(model_path), file.exists(blueprint_path))
+
+  model <- xgboost::xgb.load(model_path)
+  blueprint <- readRDS(blueprint_path)
+
+  return(list(model = model, blueprint = blueprint))
+}
+
+
+
+model_obj <- .load_model_objs("rushing_yards", version = "1.0.0")
+
+model_obj$model$params$objective <- "reg"
+
+preprocessed_pbp <- ep_preprocess(nflreadr::load_pbp(2021))
+
+rush_df <-
+  preprocessed_pbp$rush_df %>%
+  hardhat::forge(new_data = ., blueprint = model_obj$blueprint)
+
+ep_load <- rush_df$predictors %>%
+  dplyr::mutate(rushing_yards = preprocessed_pbp$rush_df$rushing_yards) %>%
+  as.matrix()
+
+ep_load <- load_ep_pbp_rush(2018:2021) %>%
+  as.matrix()
+
+rush_yards_explainer <-
+  DALEXtra::explain_xgboost(
+    model = model_obj$model,
+    data = ep_load,
+    y =  ep_load[,14])