plot.raggr: Plot function for raggr object returned by RankAggreg or...

In RankAggreg: Weighted Rank Aggregation

Description

Plots individual ordered lists with the corresponding solution. Optionally, naive average rank aggregation can be added.

Usage

## S3 method for class 'raggr'
plot(x, show.average = TRUE, show.legend = TRUE, colR="red", ...)

Arguments

x	raggr object returned by RankAggreg
show.average	boolean if average aggregation to be plotted
show.legend	boolean if the legend is to be displayed
colR	specifies the color for the resulting list
...	additional plotting parameters

Details

The function plots individual lists and the solution using ranks only (weights are not used at any time). Optional average rank aggregation can be performed and visualized. Average rank aggregation is a simple aggregation procedure which computes the average ranks for each unique element accross and orders them from the smallest to the largest value.

Value

Nothing is returned

Author(s)

Vasyl Pihur, Somnath Datta, Susmita Datta

References

Pihur, V., Datta, S., and Datta, S. (2007) "Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach" Bioinformatics, 23(13):1607-1615

See Also

RankAggreg, BruteAggreg

Examples

# rank aggregation without weights
x <- matrix(c("A", "B", "C", "D", "E",
        "B", "D", "A", "E", "C",
        "B", "A", "E", "C", "D",
        "A", "D", "B", "C", "E"), byrow=TRUE, ncol=5)

(CES <- RankAggreg(x, 5, method="CE", distance="Spearman", rho=.1, verbose=FALSE))
plot(CES)

Example output

The optimal list is: 
        B A D C E

  Algorithm:   CE
  Distance:    Spearman
  Score:       4 

RankAggreg documentation built on July 8, 2020, 6:20 p.m.