lp_spm: Link prediction with the SPM
In galanisl/LinkPrediction: Link prediction in complex networks

Description Usage Arguments Value Author(s) References Examples

Given a network of interest, it computes the likelihood score of interaction, for all disconnected node pairs, with the Structural Perturbation Method (SPM).

1	lp_spm(g, p_H = 0.1, epochs = 10, k = NA)

`g`	igraph; The network of interest.
`p_H`	numeric; Fraction of network links to remove (perturbation set).
`epochs`	integer; Number of perturbation sets to consider.
`k`	integer; If k != NA and k < N (number of network nodes), the method is approximated by computing the k larget eigenvalues instead of all N.

Tibble with the following columns:

`nodeA`	The ID of a network node.
`nodeB`	The ID of a network node.
`scr`	The likelihood score of interaction for the node pair.

Gregorio Alanis-Lobato galanisl@uni-mainz.de

Lu, L. et al. (2015) Toward link predictability of complex networks. PNAS 112(8):2325-2330

# Apply the approximated SPM link predictor to the Zachary Karate Club 
# network
spm <- lp_spm(g = karate_club, p_H = 0.1, epochs = 10, 
              k = round(sqrt(igraph::vcount(karate_club))))