predict,xgb.Booster-method

From xgboost v0.3-2 by Tong He

Predict method for eXtreme Gradient Boosting model

Predicted values based on xgboost model object.

Usage

## S3 method for class 'xgb.Booster':
predict(object, newdata, outputmargin = FALSE,
  ntreelimit = NULL)

Arguments

object: Object of class "xgb.Boost"
newdata: takes matrix, dgCMatrix, local data file or xgb.DMatrix.
outputmargin: whether the prediction should be shown in the original value of sum of functions, when outputmargin=TRUE, the prediction is untransformed margin value. In logistic regression, outputmargin=T will output value before logistic transformation.
ntreelimit: limit number of trees used in prediction, this parameter is only valid for gbtree, but not for gblinear. set it to be value bigger than 0. It will use all trees by default.

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)

Documentation reproduced from package xgboost, version 0.3-2, License: Apache License (== 2.0) | file LICENSE

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