impCML: Feature importance from Consensus Machine Learning (CML)
In metamaden/cmlmanuscript: Resource to reproduce manuscript analyses

Returns feature importance from fitting a model using CML

impCML(
  df,
  classes,
  trainindices,
  seed,
  algo.opt = c("lasso", "rf", "svm", "xgb"),
  standtable = FALSE,
  ranksummary = "median"
)

`df`	Valid data object.
`classes`	Vector of class specifying test or training set among instances.
`trainindices`	Indices of traning instances in data.
`seed`	Random seed to use in model fitting.
`algo.opt`	Algorithms to use for consensus method.
`standtable`	Boolean, whether to return a standard output table summarizing results.
`ranksummary`	Method to compute rank summary among algorithms used, currently supports 'median'.