Get a grid object from H2O distributed K/V store.

Source: R/grid.R

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.

h2o.getGrid(grid_id, sort_by, decreasing)

Arguments

grid_id	ID of existing grid object to fetch
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

Examples

# NOT RUN {
library(h2o)
library(jsonlite)
h2o.init()
iris.hex <- as.h2o(iris)
h2o.grid("gbm", grid_id = "gbm_grid_id", x = c(1:4), y = 5,
         training_frame = iris.hex, hyper_params = list(ntrees = c(1,2,3)))
grid <- h2o.getGrid("gbm_grid_id")
# Get grid summary
summary(grid)
# Fetch grid models
model_ids <- grid@model_ids
models <- lapply(model_ids, function(id) { h2o.getModel(id)})
# }