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XGBoost models

Function Works
tidypredict_fit(), tidypredict_sql(), parse_model() ✔
tidypredict_to_column() ✔
tidypredict_test() ✔
tidypredict_interval(), tidypredict_sql_interval() ✗
parsnip ✔

tidypredict_ functions

library(xgboost)

logregobj <- function(preds, dtrain) {
  labels <- xgboost::getinfo(dtrain, "label")
  preds <- 1 / (1 + exp(-preds))
  grad <- preds - labels
  hess <- preds * (1 - preds)
  return(list(grad = grad, hess = hess))
}

xgb_bin_data <- xgboost::xgb.DMatrix(
  as.matrix(mtcars[, -9]),
  label = mtcars$am
)

model <- xgboost::xgb.train(
  params = list(max_depth = 2, objective = "binary:logistic", base_score = 0.5),
  data = xgb_bin_data,
  nrounds = 50
)

Please be aware that xgboost converts data into 32-bit floats internally. This could possibly lead to splits being done incorrectly. Always verify that the predictions match up with model predictions. See this issue for more information.

parsnip

parsnip fitted models are also supported by tidypredict:

library(parsnip)

p_model <- boost_tree(mode = "regression") %>%
  set_engine("xgboost") %>%
  fit(am ~ ., data = mtcars)
#> Warning in check.deprecation(deprecated_train_params, match.call(), ...):
#> Passed invalid function arguments: nthread. These should be passed as a list to
#> argument 'params'. Conversion from argument to 'params' entry will be done
#> automatically, but this behavior will become an error in a future version.
tidypredict_test(p_model, mtcars, xg_df = xgb_bin_data)
#> tidypredict test results
#> Difference threshold: 1e-12
#> 
#>  All results are within the difference threshold

Parse model spec

Here is an example of the model spec:

pm <- parse_model(model)
str(pm, 2)
#> List of 2
#>  $ general:List of 7
#>   ..$ model        : chr "xgb.Booster"
#>   ..$ type         : chr "xgb"
#>   ..$ params       :List of 5
#>   ..$ feature_names: chr [1:10] "mpg" "cyl" "disp" "hp" ...
#>   ..$ niter        : int 50
#>   ..$ nfeatures    : int 10
#>   ..$ version      : num 1
#>  $ trees  :List of 42
#>   ..$ 0 :List of 3
#>   ..$ 1 :List of 3
#>   ..$ 2 :List of 3
#>   ..$ 3 :List of 3
#>   ..$ 4 :List of 3
#>   ..$ 5 :List of 3
#>   ..$ 6 :List of 3
#>   ..$ 7 :List of 3
#>   ..$ 8 :List of 3
#>   ..$ 9 :List of 3
#>   ..$ 10:List of 3
#>   ..$ 11:List of 2
#>   ..$ 12:List of 2
#>   ..$ 13:List of 2
#>   ..$ 14:List of 2
#>   ..$ 15:List of 2
#>   ..$ 16:List of 2
#>   ..$ 17:List of 2
#>   ..$ 18:List of 2
#>   ..$ 19:List of 2
#>   ..$ 20:List of 2
#>   ..$ 21:List of 2
#>   ..$ 22:List of 2
#>   ..$ 23:List of 2
#>   ..$ 24:List of 2
#>   ..$ 25:List of 2
#>   ..$ 26:List of 2
#>   ..$ 27:List of 2
#>   ..$ 28:List of 2
#>   ..$ 29:List of 2
#>   ..$ 30:List of 2
#>   ..$ 31:List of 2
#>   ..$ 32:List of 2
#>   ..$ 33:List of 2
#>   ..$ 34:List of 2
#>   ..$ 35:List of 2
#>   ..$ 36:List of 2
#>   ..$ 37:List of 2
#>   ..$ 38:List of 2
#>   ..$ 39:List of 2
#>   ..$ 40:List of 2
#>   ..$ 41:List of 2
#>  - attr(*, "class")= chr [1:3] "parsed_model" "pm_xgb" "list"
str(pm$trees[1])
#> List of 1
#>  $ 0:List of 3
#>   ..$ :List of 2
#>   .. ..$ prediction: num -0.436
#>   .. ..$ path      :List of 1
#>   .. .. ..$ :List of 5
#>   .. .. .. ..$ type   : chr "conditional"
#>   .. .. .. ..$ col    : chr "wt"
#>   .. .. .. ..$ val    : num 3.19
#>   .. .. .. ..$ op     : chr "less"
#>   .. .. .. ..$ missing: logi TRUE
#>   ..$ :List of 2
#>   .. ..$ prediction: num 0.429
#>   .. ..$ path      :List of 2
#>   .. .. ..$ :List of 5
#>   .. .. .. ..$ type   : chr "conditional"
#>   .. .. .. ..$ col    : chr "qsec"
#>   .. .. .. ..$ val    : num 19.4
#>   .. .. .. ..$ op     : chr "more-equal"
#>   .. .. .. ..$ missing: logi FALSE
#>   .. .. ..$ :List of 5
#>   .. .. .. ..$ type   : chr "conditional"
#>   .. .. .. ..$ col    : chr "wt"
#>   .. .. .. ..$ val    : num 3.19
#>   .. .. .. ..$ op     : chr "more-equal"
#>   .. .. .. ..$ missing: logi FALSE
#>   ..$ :List of 2
#>   .. ..$ prediction: num 0
#>   .. ..$ path      :List of 2
#>   .. .. ..$ :List of 5
#>   .. .. .. ..$ type   : chr "conditional"
#>   .. .. .. ..$ col    : chr "qsec"
#>   .. .. .. ..$ val    : num 19.4
#>   .. .. .. ..$ op     : chr "less"
#>   .. .. .. ..$ missing: logi TRUE
#>   .. .. ..$ :List of 5
#>   .. .. .. ..$ type   : chr "conditional"
#>   .. .. .. ..$ col    : chr "wt"
#>   .. .. .. ..$ val    : num 3.19
#>   .. .. .. ..$ op     : chr "more-equal"
#>   .. .. .. ..$ missing: logi FALSE

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.