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.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.