Running 'testthat.R' [111s/126s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(scoringTools)
  > 
  > test_check("scoringTools")
  Generalized Linear Model of class 'speedglm':
  
  Call:  speedglm::speedglm(formula = labels ~ ., data = df_augmente[,      -which(names(df_augmente) %in% c("poidsfinal", "classe_SCORE"))][!df_augmente$poidsfinal ==      0, ], family = stats::binomial(link = "logit"), weights = df_augmente$poidsfinal[!df_augmente$poidsfinal ==      0]) 
  
  Coefficients:
  (Intercept)          x.1          x.2  
       -0.306        2.227       -1.515  
  
  Generalized Linear Model of class 'speedglm':
  
  Call:  speedglm::speedglm(formula = stats::formula("labels ~ ."), data = Filter(function(x) (length(unique(x)) >      1), data.frame(sapply(disc[[i]]$Disc.data, as.factor), stringsAsFactors = TRUE)),      family = stats::binomial(link = "logit"), weights = NULL,      fitted = TRUE) 
  
  Coefficients:
  (Intercept)          X12          X22          X32          X33  
        0.958       -2.175       -2.069       19.731        0.270  
  
  Generalized Linear Model of class 'speedglm':
  
  Call:  speedglm::speedglm(formula = stats::formula("labels ~ ."), data = Filter(function(x) (length(unique(x)) >      1), data.frame(sapply(disc[[i]]$Disc.data, as.factor), stringsAsFactors = TRUE)),      family = stats::binomial(link = "logit"), weights = NULL,      fitted = TRUE) 
  
  Coefficients:
  (Intercept)          X12          X22          X32          X33  
        0.958       -2.175       -2.069       19.731        0.270  
  
  == Warnings ====================================================================
  -- Warning (test-augmentation.R:9:3): augmentation method works with speedglm and glm --
  non-integer #successes in a binomial glm!
  Backtrace:
   1. scoringTools::augmentation(xf, xnf, yf) test-augmentation.R:9:2
   2. speedglm::speedglm(...)
   3. speedglm::speedglm.wfit(...)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chi2.R:18:9): chi2 method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(...) test-chi2.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-chiM.R:18:9): chiM method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chiM_iter(...) test-chiM.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-fuzzy-augmentation.R:9:3): fuzzy-augmentation method works with speedglm and glm --
  non-integer #successes in a binomial glm!
  Backtrace:
   1. scoringTools::fuzzy_augmentation(xf, xnf, yf) test-fuzzy-augmentation.R:9:2
   2. speedglm::speedglm(...)
   3. speedglm::speedglm.wfit(...)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-mdlp.R:18:9): mdlp method works with speedglm and glm ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::mdlp_iter(...) test-mdlp.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:17:3): show method for reject works -----------------
  non-integer #successes in a binomial glm!
  Backtrace:
   1. scoringTools::augmentation(xf, xnf, yf) test-methods.R:17:2
   2. speedglm::speedglm(...)
   3. speedglm::speedglm.wfit(...)
  -- Warning (test-methods.R:33:3): show method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:33:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:33:3): show method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:33:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:33:3): show method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:33:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:33:3): show method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:33:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:33:3): show method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:33:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:33:3): show method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:33:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:51:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:51:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:51:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:51:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:51:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:51:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:51:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:51:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:51:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:51:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:51:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:51:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:52:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. stats::predict(object = chi2_modele, newdata = data.frame(x)) test-methods.R:52:2
    2. scoringTools::predict(object = chi2_modele, newdata = data.frame(x))
    3. scoringTools:::.local(object, ...)
   13. scoringTools:::discretize_cutp(...)
   14. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   17. base::order(min_cutoff)
   18. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   19. base:::FUN(X[[i]], ...)
   22. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:52:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. stats::predict(object = chi2_modele, newdata = data.frame(x)) test-methods.R:52:2
    2. scoringTools::predict(object = chi2_modele, newdata = data.frame(x))
    3. scoringTools:::.local(object, ...)
   13. scoringTools:::discretize_cutp(...)
   14. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   17. base::order(max_cutoff)
   18. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   19. base:::FUN(X[[i]], ...)
   22. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:52:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. stats::predict(object = chi2_modele, newdata = data.frame(x)) test-methods.R:52:2
    2. scoringTools::predict(object = chi2_modele, newdata = data.frame(x))
    3. scoringTools:::.local(object, ...)
   13. scoringTools:::discretize_cutp(...)
   14. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   17. base::order(min_cutoff)
   18. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   19. base:::FUN(X[[i]], ...)
   22. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:52:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. stats::predict(object = chi2_modele, newdata = data.frame(x)) test-methods.R:52:2
    2. scoringTools::predict(object = chi2_modele, newdata = data.frame(x))
    3. scoringTools:::.local(object, ...)
   13. scoringTools:::discretize_cutp(...)
   14. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   17. base::order(max_cutoff)
   18. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   19. base:::FUN(X[[i]], ...)
   22. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:52:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. stats::predict(object = chi2_modele, newdata = data.frame(x)) test-methods.R:52:2
    2. scoringTools::predict(object = chi2_modele, newdata = data.frame(x))
    3. scoringTools:::.local(object, ...)
   13. scoringTools:::discretize_cutp(...)
   14. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   17. base::order(min_cutoff)
   18. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   19. base:::FUN(X[[i]], ...)
   22. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:52:3): predict method for discretization works ------
  cannot xtfrm data frames
  Backtrace:
    1. stats::predict(object = chi2_modele, newdata = data.frame(x)) test-methods.R:52:2
    2. scoringTools::predict(object = chi2_modele, newdata = data.frame(x))
    3. scoringTools:::.local(object, ...)
   13. scoringTools:::discretize_cutp(...)
   14. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   17. base::order(max_cutoff)
   18. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   19. base:::FUN(X[[i]], ...)
   22. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:66:3): predict method for reject inference works ----
  non-integer #successes in a binomial glm!
  Backtrace:
   1. scoringTools::augmentation(xf, xnf, yf) test-methods.R:66:2
   2. speedglm::speedglm(...)
   3. speedglm::speedglm.wfit(...)
  -- Warning (test-methods.R:73:3): predict method for reject inference works ----
  non-integer #successes in a binomial glm!
  Backtrace:
   1. scoringTools::augmentation(data.frame(xf), data.frame(xnf), yf) test-methods.R:73:2
   2. speedglm::speedglm(...)
   3. speedglm::speedglm.wfit(...)
  -- Warning (test-methods.R:93:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:93:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:93:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:93:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:95:3): plot method for discretization works ---------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y, validation = TRUE) test-methods.R:95:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (???): plot method for discretization works -------------------------
  Package 'plotly' suggested but not installed, falling back to 'graphics' package.
  Backtrace:
   1. testthat::expect_error(base_plot <- plot(x = chi2_modele, type = "ROC"))
   7. scoringTools::plot(x = chi2_modele, type = "ROC")
   8. scoringTools:::.local(x, ...)
  -- Warning (???): plot method for discretization works -------------------------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y)
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (???): plot method for discretization works -------------------------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y)
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (???): plot method for discretization works -------------------------
  Package 'plotly' suggested but not installed, falling back to 'graphics' package.
  Backtrace:
   1. testthat::expect_error(base_plot <- plot(x = chi2_modele, type = "discretization"))
   7. scoringTools::plot(x = chi2_modele, type = "discretization")
   8. scoringTools:::.local(x, ...)
  -- Warning (???): plot method for discretization works -------------------------
  Package 'plotly' suggested but not installed, falling back to 'graphics' package.
  Backtrace:
   1. testthat::expect_error(base_plot <- plot(x = chi2_modele, type = "lift"))
   7. scoringTools::plot(x = chi2_modele, type = "lift")
   8. scoringTools:::.local(x, ...)
  -- Warning (???): plot method for discretization works -------------------------
  Speedglm not installed, using glm instead (slower).
  Backtrace:
   1. scoringTools::chi2_iter(x, y)
  -- Warning (???): plot method for discretization works -------------------------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y)
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (???): plot method for discretization works -------------------------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y)
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (???): plot method for discretization works -------------------------
  Package 'plotly' suggested but not installed, falling back to 'graphics' package.
  Backtrace:
   1. base::plot(x = chi2_modele, type = "glm")
   2. scoringTools::plot(x = chi2_modele, type = "glm")
   3. scoringTools:::.local(x, ...)
  -- Warning (test-methods.R:145:3): discretize method for discretization works --
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:145:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:145:3): discretize method for discretization works --
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::chi2_iter(x, y) test-methods.R:145:2
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:147:3): discretize method for discretization works --
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::discretize(chi2_modele, x) test-methods.R:147:2
    2. scoringTools::discretize(chi2_modele, x)
    3. scoringTools:::discretize_cutp(...)
    4. scoringTools:::get_cutp(disc_train_set, cont_train_set)
    7. base::order(min_cutoff)
    8. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
    9. base:::FUN(X[[i]], ...)
   12. base::xtfrm.data.frame(x)
  -- Warning (test-methods.R:147:3): discretize method for discretization works --
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::discretize(chi2_modele, x) test-methods.R:147:2
    2. scoringTools::discretize(chi2_modele, x)
    3. scoringTools:::discretize_cutp(...)
    4. scoringTools:::get_cutp(disc_train_set, cont_train_set)
    7. base::order(max_cutoff)
    8. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
    9. base:::FUN(X[[i]], ...)
   12. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(min_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  -- Warning (test-topdown.R:18:9): topdown method works with speedglm -----------
  cannot xtfrm data frames
  Backtrace:
    1. scoringTools::topdown_iter(...) test-topdown.R:18:8
    6. scoringTools:::discretize_cutp(...)
    7. scoringTools:::get_cutp(disc_train_set, cont_train_set)
   10. base::order(max_cutoff)
   11. base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   12. base:::FUN(X[[i]], ...)
   15. base::xtfrm.data.frame(x)
  
  == Failed tests ================================================================
  -- Error (test-topdown.R:18:9): topdown method works with speedglm -------------
  Error: factor X1 has new levels 3
  Backtrace:
      x
   1. \-scoringTools::topdown_iter(...) test-topdown.R:18:8
   2.   +-scoringTools::normalizedGini(...)
   3.   | \-scoringTools:::Gini(actual, predicted)
   4.   +-stats::predict(best.disc[[1]], data_test, type = "response")
   5.   +-stats::predict(best.disc[[1]], data_test, type = "response")
   6.   \-speedglm::predict.speedglm(best.disc[[1]], data_test, type = "response")
   7.     \-speedglm::predict.speedlm(...)
   8.       +-stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   9.       \-stats::model.frame.default(...)
  
  [ FAIL 1 | WARN 170 | SKIP 0 | PASS 487 ]
  Error: Test failures
  Execution halted