borda: Borda based rank aggregation

In TopKLists: Inference, Aggregation and Visualization for Top-K Ranked Lists

Borda based rank aggregation

Description

Computes Borda scores and ranks based on four different aggregation functions.

Usage

Borda(input, space = NULL, k = NULL)

Arguments

input	A list containing individual ranked lists.
space	A list containing the underlying spaces. If not explicitly specified, all lists are treated as coming from a common space defined by the union of all input lists.
k	An integer specifying the number of items in the output top-k list.

Details

Computes Borda scores and ranks based on four different aggregation functions, in which the underlying spaces, where the individual ranked lists come from, are taken into account. The four aggregation functions are mean, median, geometric mean, and L2 norm.

Value

A list with two components:

TopK	A matrix with 4 columns each corresponding to the rankings by each of the 4 aggregation functions.
Scores	A matrix with 4 columns each corresponding to the Borda scores from each of the 4 aggregation functions

Author(s)

Shili Lin <[e-mail]>

References

Lin, S. (2010). Space oriented rank-based data integration. Statistical Applications in Genetics and Molecular Biology 9, Article 20.

See Also

geo.mean, l2norm

Examples

#get sample data
data(TopKSpaceSampleInput)

outBorda=Borda(input,space) #underlying space-dependent
outBorda1=Borda(input,space=input) #top-k spaces

TopKLists documentation built on Sept. 1, 2022, 5:10 p.m.