Error in GP_deviance(beta = row, X = X, Y = Y, nug_thres = nug_thres, : Infinite values of the Deviance Function, unable to find optimum parameters

[hbaniecki]

Windows 10, R v4.1, forester v1.0.0 (fresh install - newest dependencies)

Error message:

Error in GP_deviance(beta = row, X = X, Y = Y, nug_thres = nug_thres,  : 
  Infinite values of the Deviance Function, 
            unable to find optimum parameters 

Code:

load(file = "dane_short_nefro.rda")
df_raw <- dane_short
colnames(df_raw)
colnames(df_raw) <- c("aki", "covid_goraczka", "covid_oddechowe", "covid_pokarmowy",
                      "covid_neurologiczne", "nadcisnienie", "cukrzyca", "miazdzyca_serca",
                      "hiperlipidemia", "kreatynina", "mioglobina", "aki_wywiad", 
                      "respirator", "pchn")

table(df_raw$aki_wywiad)
table(df_raw$aki, df_raw$aki_wywiad)

df <- df_raw[df_raw$aki_wywiad == 0, colnames(df_raw) != "aki_wywiad"]
dim(df)
table(df$aki)

library(forester)
set.seed(123)
# df$aki <- factor(df$aki) ## without this returns an error
best_model <- forester(
  data = df, 
  target = "aki", 
  type = "classification",
  metric = "precision", 
  tune = TRUE
)

@lhthien09 has the data.

[lhthien09]

Hi, this problem comes from rBayesianOptimization package, whentune = TRUE, we will investigate and add constraints to avoid this.