out <- train(super_label ~ .,
data = train.df,
method = glm_h2o,
preProc = c("center", "scale"),
# trControl = trainControl(method = "none",classProbs = TRUE, savePredictions = "final"),
trControl = trainControl(method = "cv", number = 4, classProbs = TRUE, summaryFunction = twoClassSummary, seeds = NA, savePredictions ="final"),
metric = 'ROC',
tuneGrid = data.frame(
solver = "COORDINATE_DESCENT",
max_iterations = 19,
objective_epsilon = 1e-04,
gradient_epsilon = 1e-06,
link = "logit",
lambda_min_ratio = 1e-04,
max_active_predictors = 5000,
obj_reg = 0.025,
alpha = 0, lambda = 2.1098, lambda_search = FALSE
)
)
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