r descr_models("rand_forest", "spark")
defaults <- tibble::tibble(parsnip = c("mtry", "trees", "min_n"), default = c("see below", "20L", "1L")) param <- rand_forest() %>% set_engine("spark") %>% make_parameter_list(defaults)
This model has r nrow(param)
tuning parameters:
param$item
mtry
depends on the number of columns and the model mode. The default in [sparklyr::ml_random_forest()] is floor(sqrt(ncol(x)))
for classification and floor(ncol(x)/3)
for regression.
rand_forest( mtry = integer(1), trees = integer(1), min_n = integer(1) ) %>% set_engine("spark") %>% set_mode("regression") %>% translate()
min_rows()
and min_cols()
will adjust the number of neighbors if the chosen value if it is not consistent with the actual data dimensions.
rand_forest( mtry = integer(1), trees = integer(1), min_n = integer(1) ) %>% set_engine("spark") %>% set_mode("classification") %>% translate()
Note that, for spark engines, the case_weight
argument value should be a character string to specify the column with the numeric case weights.
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.