topTable-methods: Methods for topTable

In nlcv: Nested Loop Cross Validation

Description

Methods for topTable. topTable extracts the top n most important features for a given classification or regression procedure.

Usage

## S4 method for signature 'nlcv'
topTable(fit, n = 5, method = "percentage")

Arguments

fit	object resulting from a classification or regression procedure
n	number of features that one wants to extract from a table that ranks all features according to their importance in the classification or regression model
method	method used to rank the features; one of percentage (percentage of runs the feature is selected in the top n), meanrank (mean rank of the feature across runs) or medianrank (median rank of the feature across runs); percentage is the default method

Details

The top n features are extracted across all runs of the nested loop cross-validation. After ranking on their frequency of selection, the top n are retained and returned.

Value

a data frame of one column (percentage) with percentages reflecting the frequency of selection of a feature in the top n across all runs; the features are sorted on decreasing frequency.

Methods

nlcv

fit = "nlcv"

nlcv objects are produced by nlcv

Author(s)

Willem Talloen and Tobias Verbeke

Examples

  data(nlcvRF_SS)
  topTable(nlcvRF_SS, n = 7, method = "medianrank")

nlcv documentation built on May 2, 2019, 7:28 a.m.