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El Potaeto 2015-02-10 19:46:39 +01:00
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R-package/vignettes/xgboostPresentation.Rmd
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@ -83,23 +83,24 @@ Xgboost offer a way to group them in a `xgb.DMatrix`. You can even add other met
```{r trainingDense, message=F, warning=F} ```{r trainingDense, message=F, warning=F}
dtrain <- xgb.DMatrix(data = train$data, label = train$label) dtrain <- xgb.DMatrix(data = train$data, label = train$label)
bst <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2, objective = "binary:logistic") bstDMatrix <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2, objective = "binary:logistic")
``` ```
# Verbose = 0,1,2 Below is a demonstration of the effect of verbose parameter.
```{r trainingVerbose, message=T, warning=F}
print ('train xgboost with verbose 0, no message') print ('train xgboost with verbose 0, no message')
bst <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2, bst <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2,
objective = "binary:logistic", verbose = 0) objective = "binary:logistic", verbose = 0)
print ('train xgboost with verbose 1, print evaluation metric') print ('train xgboost with verbose 1, print evaluation metric')
bst <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2, bst <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2,
objective = "binary:logistic", verbose = 1) objective = "binary:logistic", verbose = 1)
print ('train xgboost with verbose 2, also print information about tree') print ('train xgboost with verbose 2, also print information about tree')
bst <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2, bst <- xgboost(data = dtrain, max.depth = 2, eta = 1, nround = 2,
objective = "binary:logistic", verbose = 2) objective = "binary:logistic", verbose = 2)
```
# you can also specify data as file path to a LibSVM format input
# since we do not have this file with us, the following line is just for illustration
# bst <- xgboost(data = 'agaricus.train.svm', max.depth = 2, eta = 1, nround = 2,objective = "binary:logistic")
#--------------------basic prediction using xgboost-------------- #--------------------basic prediction using xgboost--------------
# you can do prediction using the following line # you can do prediction using the following line