Usage
xgboost(data = NULL, label = NULL, missing = NULL, params = list(),
nrounds, verbose = 1, print.every.n = 1L, early.stop.round = NULL,
maximize = NULL, ...)
Arguments
data
takes matrix
, dgCMatrix
, local data file or
xgb.DMatrix
.
label
the response variable. User should not set this field,
if data is local data file or xgb.DMatrix
.
missing
Missing is only used when input is dense matrix, pick a float
value that represents missing value. Sometimes a data use 0 or other extreme value to represents missing values.
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
print.every.n
Print every N progress messages when verbose>0
. Default is 1 which means all messages are printed.
early.stop.round
If NULL
, the early stopping function is not triggered.
If set to an integer k
, training with a validation set will stop if the performance
keeps getting worse consecutively for k
rounds.
maximize
If feval
and early.stop.round
are set, then maximize
must be set as well.
maximize=TRUE
means the larger the evaluation score the better.
...
other parameters to pass to params
.