Note that if neither cross-validation nor a validation frame is used in the grid search, then the training metrics will display in the "get grid" output. If a validation frame is passed to the grid, and nfolds = 0, then the validation metrics will display. However, if nfolds > 1, then cross-validation metrics will display even if a validation frame is provided.
sort_by: Sort the models in the grid space by a metric. Choices are "logloss", "residual_deviance", "mse", "auc", "accuracy", "precision", "recall", "f1", etc.
decreasing: Specify whether sort order should be decreasing
verbose: Controls verbosity of the output, if enabled prints out error messages for failed models (default: FALSE)
Examples
## Not run:library(h2o)library(jsonlite)h2o.init()iris_hf <- as.h2o(iris)h2o.grid("gbm", grid_id ="gbm_grid_id", x = c(1:4), y =5, training_frame = iris_hf, hyper_params = list(ntrees = c(1,2,3)))grid <- h2o.getGrid("gbm_grid_id")# Get grid summarysummary(grid)# Fetch grid modelsmodel_ids <- grid@model_ids
models <- lapply(model_ids,function(id){ h2o.getModel(id)})## End(Not run)