evaluate_links: Evaluate Link Predictions Against Known Edges

In Nestimate: Network Estimation, Bootstrap, and Higher-Order Analysis

Evaluate Link Predictions Against Known Edges

Description

Computes AUC-ROC, precision@k, and average precision for link predictions against a set of known true edges.

Usage

evaluate_links(pred, true_edges, k = c(5L, 10L, 20L))

Arguments

pred	A net_link_prediction object.
true_edges	A data frame with columns from and to, or a binary matrix where 1 indicates a true edge.
k	Integer vector. Values of k for precision@k. Default: c(5, 10, 20).

Value

A data frame with columns: method, auc, average_precision, and one precision_at_k column per k value.

Examples

set.seed(42)
seqs <- data.frame(
  V1 = sample(LETTERS[1:5], 50, TRUE),
  V2 = sample(LETTERS[1:5], 50, TRUE),
  V3 = sample(LETTERS[1:5], 50, TRUE)
)
net <- build_network(seqs, method = "relative")
pred <- predict_links(net, exclude_existing = FALSE)

# Evaluate: predict the network's own edges
true <- data.frame(from = pred$predictions$from[1:5],
                   to = pred$predictions$to[1:5])
evaluate_links(pred, true)

Nestimate documentation built on April 20, 2026, 5:06 p.m.