# title : H2OGBM_StopRules
# author : jacob
# desc :
h2o.rm("H2OGBM_StopRules")
hyper_params <- list(
stopping_rounds = c(1, 2, 3, 5),
stopping_tolerance = c(0.01, 0.05, 0.001)
)
grid <- h2o.grid(
algorithm = "gbm",
grid_id = "H2OGBM_StopRules",
x = x, y = y, seed = 1234,
training_frame = train_hex,
validation_frame = valid_hex,
score_each_iteration = TRUE,
stopping_metric = "logloss",
ntrees = 10000,
hyper_params = hyper_params,
search_criteria = list(strategy = "Cartesian")
)
grid_sorted <- h2o.getGrid(grid_id="H2OGBM_StopRules", sort_by="logloss", decreasing=FALSE)
autoGBM_Models["H2OGBM_StopRules"] <- list(h2o.getModel(grid_sorted@model_ids[[1]]))
h2o.auc(h2o.performance(autoGBM_Models["H2OGBM_StopRules"][[1]], newdata = test_hex))
saveRDS(autoGBM_Models['H2OGBM_StopRules'], file.path(model_path, "H2OGBM_StopRules.rda"))
autoGBM_BestParams['stopping_rounds'] <- as.numeric(grid_sorted@summary_table$stopping_rounds[1])
autoGBM_BestParams['stopping_tolerance'] <- as.numeric(grid_sorted@summary_table$stopping_tolerance[1])
cat(">> H2OGBM_StopRules done! \n")
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