xgboost
From xgboost v0.3-2
by Tong He
eXtreme Gradient Boosting (Tree) library
A simple interface for xgboost in R
Usage
xgboost(data = NULL, label = NULL, params = list(), nrounds,
verbose = 1, ...)
Arguments
- data
- takes
matrix
,dgCMatrix
, local data file orxgb.DMatrix
. - label
- the response variable. User should not set this field,
- params
- the list of parameters. Commonly used ones are:
objective
objective function, common ones arereg:linear
linear regressionbinary:logistic
logistic regression for classification
- nrounds
- the max number of iterations
- verbose
- If 0, xgboost will stay silent. If 1, xgboost will print information of performance. If 2, xgboost will print information of both performance and construction progress information
- ...
- other parameters to pass to
params
.
Details
This is the modeling function for xgboost.
Parallelization is automatically enabled if OpenMP is present. Number of threads can also be manually specified via "nthread" parameter
Examples
data(agaricus.train, package='xgboost')
data(agaricus.test, package='xgboost')
train <- agaricus.train
test <- agaricus.test
bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
eta = 1, nround = 2,objective = "binary:logistic")
pred <- predict(bst, test$data)
Community examples
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