axe-xgb.Booster {butcher} | R Documentation |
Axing a xgb.Booster.
Description
xgb.Booster objects are created from the xgboost package,
which provides efficient and scalable implementations of gradient
boosted decision trees. Given the reliance of post processing
functions on the model object, like xgb.Booster.complete
,
on the first class listed, the butcher_xgb.Booster
class is
not appended.
Usage
## S3 method for class 'xgb.Booster'
axe_call(x, verbose = FALSE, ...)
## S3 method for class 'xgb.Booster'
axe_env(x, verbose = FALSE, ...)
Arguments
x |
A model object. |
verbose |
Print information each time an axe method is executed.
Notes how much memory is released and what functions are
disabled. Default is |
... |
Any additional arguments related to axing. |
Value
Axed xgb.Booster object.
Examples
library(xgboost)
library(parsnip)
data(agaricus.train)
bst <- xgboost(data = agaricus.train$data,
label = agaricus.train$label,
eta = 1,
nthread = 2,
nrounds = 2,
eval_metric = "logloss",
objective = "binary:logistic",
verbose = 0)
out <- butcher(bst, verbose = TRUE)
# Another xgboost model
fit <- boost_tree(mode = "classification", trees = 20) %>%
set_engine("xgboost", eval_metric = "mlogloss") %>%
fit(Species ~ ., data = iris)
out <- butcher(fit, verbose = TRUE)
[Package butcher version 0.3.4 Index]