mlho.it: iterative modeling with MLHO

In hestiri/mlho: Machine Learning for Health Outcomes (MLHO)

iterative modeling with MLHO

Description

iterative modeling with MLHO

Usage

mlho.it(
  dbmart,
  labels = labeldt,
  dems = NULL,
  test.sample = 30,
  MSMR.binarize = FALSE,
  MSMR.sparsity = 0.005,
  MSMR.jmi = TRUE,
  MSMR.topn = 200,
  mlearn.save.model = FALSE,
  mlearn.note = "mlho_phewas run",
  mlearn.aoi = "demo",
  mlearn.cv = "cv",
  mlearn.nfold = 5,
  multicore = FALSE,
  preProc = TRUE,
  iterations = 5
)

Arguments

dbmart	dbmart table
labels	should be the labeldt table
dems	table containing the demographic variables
test.sample	put 20 if you want to use 20 percent for testing and 80 percent for training
MSMR.binarize	MSMR.lite parameter
MSMR.sparsity	MSMR.lite parameter
MSMR.jmi	MSMR.lite parameter
MSMR.topn	MSMR.lite parameter
mlearn.save.model	mlearn parameter
mlearn.note	mlearn parameter
mlearn.aoi	mlearn parameter
mlearn.cv	mlearn parameter
mlearn.nfold	mlearn parameter
multicore	if you want to parallelize the process
preProc	preprocessig on the train data or not
iterations	number of iterations you want. recommended at least 5. needs to be numeric

hestiri/mlho documentation built on March 20, 2023, 11:04 p.m.