rfgini: Random Forest cumulative MeanDecreaseGini feature selection....

In feamiR: Classification and Feature Selection for microRNA/mRNA Interactions

Description

Random Forest cumulative MeanDecreaseGini feature selection. Implements a feature selection approach based on cumulative MeanDecreaseGini using Random Forests trained on multiple subsamples.

Usage

rfgini(num_runs = 100, num_trees = 30, file_path = file_path)

Arguments

num_runs	Number of subsamples to use for voting scheme (default: 100)
num_trees	Number of trees for random forest (selected using select_rf_numtrees)
file_path	Where the num_runs subsample files are found (e.g. if sample 10 is at 'subsamples/sample10.csv' then file_path should be 'subsamples/sample'). There must be enough samples to fulfill num_runs runs.

Value

The function will output a data.frame with cumulative mean decrease in Gini for each feature in the first columns (each row is a feature) and the rest of the column containing mean decrease in Gini for each of the num_runs runs.

Examples

rfgini(
  num_runs=5,
  num_trees=30,
  file_path=paste(system.file('samples/subsamples',package = "feamiR"),'/sample',sep=''))

feamiR documentation built on Jan. 19, 2021, 9:08 a.m.