I was following instruction for tuning XGBoost with tidymodels by Julia Silge and I'm trying to adapt my NBA DFS data and I keep running into the "All models failed" error. Can you help me figure out the issue? I've posted my code below.
Jan29 <- read.csv("nbaJan29a.csv", header = TRUE)
> Jan29$Position <- as.numeric(Jan29$Position)
> Jan29$First.Name <- as.numeric(Jan29$First.Name)
> Jan29$Nickname <- as.numeric(Jan29$Nickname)
> Jan29$Last.Name <- as.numeric(Jan29$Last.Name)
> Jan29$Played <- as.numeric(Jan29$Played)
> Jan29$Salary <- as.numeric(Jan29$Salary)
> Jan29$RFMin <- as.numeric(Jan29$RFMin)
> Jan29$Team <- as.numeric(Jan29$Team)
> Jan29$Opponent <- as.numeric(Jan29$Opponent)
>
> View(Jan29)
>
> library(tidymodels)
> set.seed(123)
>
> nba_split <- initial_split(Jan29, strata = Today.s.Score)
> nba_train <- training(nba_split)
> nba_test <- testing(nba_split)
>
> xgb_spec <- boost_tree(trees = 1000,tree_depth = tune(),min_n = tune(),loss_reduction = tune(),sample_size = tune(),mtry = tune(),learn_rate = tune(),) %>% set_engine("xgboost")%>%set_mode("regression")
>
>
> xgb_grid <- grid_latin_hypercube(tree_depth(),min_n(),loss_reduction(),sample_size = sample_prop(),finalize(mtry(),nba_train),learn_rate(),size = 20)
>
> xgb_wf <- workflow() %>% add_formula(Today.s.Score ~ .)%>% add_model(xgb_spec)
>
>
> set.seed(123)
> nba_folds <- vfold_cv(nba_train, strata = Today.s.Score)
> nba_folds
# 10-fold cross-validation using stratification
# A tibble: 10 x 2
splits id
<list> <chr>
1 <split [1.3k="" 144]=""> Fold01
2 <split [1.3k="" 144]=""> Fold02
3 <split [1.3k="" 144]=""> Fold03
4 <split [1.3k="" 142]=""> Fold04
5 <split [1.3k="" 142]=""> Fold05
6 <split [1.3k="" 141]=""> Fold06
7 <split [1.3k="" 141]=""> Fold07
8 <split [1.3k="" 140]=""> Fold08
9 <split [1.3k="" 140]=""> Fold09
10 <split [1.3k="" 140]=""> Fold10
>
> doParallel::registerDoParallel()
> set.seed(234)
> xbg_res <- tune_grid(xgb_wf,resamples = nba_folds,grid = xgb_grid,control = control_grid(save_pred = TRUE))
Warning message:
All models failed. See the `.notes` column.