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R-package/demo/predict_first_ntree.R

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+require(xgboost)
+# load in the agaricus dataset
+data(agaricus.train, package='xgboost')
+data(agaricus.test, package='xgboost')
+dtrain <- xgb.DMatrix(agaricus.train$data, label = agaricus.train$label)
+dtest <- xgb.DMatrix(agaricus.test$data, label = agaricus.test$label)
+
+param <- list(max_depth=2,eta=1,silent=1,objective='binary:logistic')
+watchlist <- list(eval = dtest, train = dtrain)
+nround = 2
+
+# training the model for two rounds
+bst = xgb.train(param, dtrain, nround, watchlist)
+cat('start testing prediction from first n trees\n')
+labels <- getinfo(dtest,'label')
+
+### predict using first 1 tree
+ypred1 = predict(bst, dtest, ntreelimit=1)
+# by default, we predict using all the trees
+ypred2 = predict(bst, dtest)
+
+cat('error of ypred1=', mean(as.numeric(ypred1>0.5)!=labels),'\n')
+cat('error of ypred2=', mean(as.numeric(ypred2>0.5)!=labels),'\n')