Created
January 25, 2019 11:55
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Testing GPU set up in R for machine learning
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library(xgboost) | |
# load data | |
data(agaricus.train, package = 'xgboost') | |
data(agaricus.test, package = 'xgboost') | |
train <- agaricus.train | |
test <- agaricus.test | |
# fit model | |
bst <- xgboost(data = train$data, label = train$label, max_depth = 5, eta = 0.001, nrounds = 1000, | |
nthread = 2, objective = "binary:logistic", tree_method = "gpu_hist") | |
# predict | |
pred <- predict(bst, test$data) | |
library(h2o) | |
h2o.init() | |
# Run regression GBM on australia data | |
australia_path <- system.file("extdata", "australia.csv", package = "h2o") | |
australia <- h2o.uploadFile(path = australia_path) | |
independent <- c("premax", "salmax","minairtemp", "maxairtemp", "maxsst", | |
"maxsoilmoist", "Max_czcs") | |
dependent <- "runoffnew" | |
h2o.gbm(y = dependent, x = independent, training_frame = australia, | |
ntrees = 1000, max_depth = 3, min_rows = 2) | |
h2o.xgboost(y = dependent, x = independent, training_frame = australia, | |
ntrees = 1000, backend = "cpu") | |
h2o.xgboost(y = dependent, x = independent, training_frame = australia, | |
ntrees = 1000, backend = "gpu") |
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