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