impBorutaCML: Feature importance from Consensus Machine Learning (CML)...

In metamaden/cmlmanuscript: Resource to reproduce manuscript analyses

Description

Returns feature importance from fitting a model using CML with the Boruta method.

Usage

impBorutaCML(
  x = x,
  y = y,
  seed,
  algo.opt = c("lasso", "rf", "svm", "xgb"),
  ranksummary = "median"
)

Arguments

x	Valid data object.
y	Vector of classes among instances in data object.
seed	Random seed to use in model fitting.
algo.opt	Algorithms to use for consensus method.
ranksummary	Method to compute rank summary among algorithms used, currently supports 'median'.

Value

Consensus feature importance.

metamaden/cmlmanuscript documentation built on Dec. 12, 2019, 7:53 a.m.