R: Setup a grid search for xgboost (!!)

January 7, 2016

(This article was first published on R – The Hack-R Blog, and kindly contributed to R-bloggers)

I find this code super useful because R’s implementation of xgboost (and to my knowledge Python’s) otherwise lacks support for a grid search:

# set up the cross-validated hyper-parameter search
xgb_grid_1 = expand.grid(
nrounds = 1000,
eta = c(0.01, 0.001, 0.0001),
max_depth = c(2, 4, 6, 8, 10),
gamma = 1

# pack the training control parameters
xgb_trcontrol_1 = trainControl(
method = "cv",
number = 5,
verboseIter = TRUE,
returnData = FALSE,
returnResamp = "all",                                                        # save losses across all models
classProbs = TRUE,                                                           # set to TRUE for AUC to be computed
summaryFunction = twoClassSummary,
allowParallel = TRUE

# train the model for each parameter combination in the grid,
#   using CV to evaluate
xgb_train_1 = train(
x = as.matrix(df_train %>%
y = as.factor(df_train$SeriousDlqin2yrs),
trControl = xgb_trcontrol_1,
tuneGrid = xgb_grid_1,
method = "xgbTree"

# scatter plot of the AUC against max_depth and eta
ggplot(xgb_train_1$results, aes(x = as.factor(eta), y = max_depth, size = ROC, color = ROC)) +
geom_point() +
theme_bw() +
scale_size_continuous(guide = "none")


To leave a comment for the author, please follow the link and comment on their blog: R – The Hack-R Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)