gpb.get.eval.result: Get record evaluation result from booster

In gpboost: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models

Get record evaluation result from booster

Description

Given a gpb.Booster, return evaluation results for a particular metric on a particular dataset.

Usage

gpb.get.eval.result(booster, data_name, eval_name, iters = NULL,
  is_err = FALSE)

Arguments

booster	Object of class gpb.Booster
data_name	Name of the dataset to return evaluation results for.
eval_name	Name of the evaluation metric to return results for.
iters	An integer vector of iterations you want to get evaluation results for. If NULL (the default), evaluation results for all iterations will be returned.
is_err	TRUE will return evaluation error instead

Value

numeric vector of evaluation result

Examples

# train a regression model
data(agaricus.train, package = "gpboost")
train <- agaricus.train
dtrain <- gpb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "gpboost")
test <- agaricus.test
dtest <- gpb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2")
valids <- list(test = dtest)
model <- gpb.train(
  params = params
  , data = dtrain
  , nrounds = 5L
  , valids = valids
  , min_data = 1L
  , learning_rate = 1.0
)

# Examine valid data_name values
print(setdiff(names(model$record_evals), "start_iter"))

# Examine valid eval_name values for dataset "test"
print(names(model$record_evals[["test"]]))

# Get L2 values for "test" dataset
gpb.get.eval.result(model, "test", "l2")

gpboost documentation built on Oct. 24, 2023, 9:09 a.m.