getImportanceScores: Compute and return importance scores (Relief-F scores)

In insilico/privateEC: Privacy Preserving Evaporative Cooling Feature Selection and Classification with Relief-F and Random Forests

Description

Compute and return importance scores (Relief-F scores)

Usage

getImportanceScores(
  train.set = NULL,
  holdout.set = NULL,
  label = "class",
  importance.name = "relieff",
  importance.algorithm = "ReliefFequalK",
  relief.k.method = "k_half_sigma",
  verbose = FALSE
)

Arguments

train.set	A training data frame with last column as outcome
holdout.set	A holdout data frame with last column as outcome
label	A character vector of the outcome variable column name. class/qtrait for classification/regression
importance.name	A list importance operation parameters
importance.algorithm	A character vector of the ReliefF estimator
relief.k.method	A character of numeric to indicate number of nearest neighbors for relief algorithm. Possible characters are: k_half_sigma (floor((num.samp-1)*0.154)), m6 (floor(num.samp/6)), myopic (floor((num.samp-1)/2)), and m4 (floor(num.samp/4))
verbose	A flag indicating whether verbose output be sent to stdout

Value

A list with two data frames representing the importance scores (Relief-F scores) for the train and holdout data sets.

See Also

Other classification: epistasisRank(), originalThresholdout(), privateEC(), privateRF(), standardRF(), xgboostRF()

insilico/privateEC documentation built on May 22, 2020, 5:12 p.m.