trainClassifier: The training model with cds and 3' UTRs as random forest
In Roleren/uORFomePipe: uORF prediction in R

trainClassifier

R Documentation

The training model with cds and 3' UTRs as random forest

Description

The training model with cds and 3' UTRs as random forest

Usage

trainClassifier(
  tissue,
  ip = "localhost",
  port = 54321,
  nthreads_h2o = max(min(45, as.integer(BiocParallel::bpparam()$workers/2)), 1),
  max_mem_size = "200G"
)

Arguments

`tissue`	Tissues to train on, use "combined" if you want all in one
`ip`	h2o cluster ip, default: "localhost".
`port`	h2o cluster port, default: 54321
`nthreads_h2o`	number of cores for H20. Default: `max(min(45, as.integer(BiocParallel::bpparam()$workers/2)), 1)`
`max_mem_size`	max allowed memory for H20: default ("200G")