best_matches | R Documentation |
Rank vertex-pairs in order of a goodness of matching metric
best_matches(A, B, match, measure, num = NULL, true_label = NULL)
A |
A matrix, an |
B |
A matrix, an |
match |
graphMatch, eg result of call to gm |
measure |
One of "row_cor", "row_diff", or "row_perm_stat" or a function (see details). Measure for computing goodness of matching. |
num |
A positive integer or NULL. Number of pairs of best matched vertices needed. NULL indicates all matches. |
true_label |
the true correspondence (if available). |
If measure is a function, it should take exactly two matrices or igraph objects as arguments and return a vector of length equal to the number of nonseed nodes in the first object. Smaller values will be taken to indicate better matches.
best_matches
returns a data frame with the indices of best
matched vertices in G_1
named A_best
, the indices of best
matched vertices in G_2
named B_best
and the values of measure
for best matches, where smaller values indicate better matches for all
measures. If the true correspondence is available, also returns the
precision of top n best matches, for each n <= num
.
row_cor
takes 1 minus the row correlation value for the corresponding vertex.
row_diff
takes the row difference value for each corresponding vertex.
row_perm_stat
uses the row permutation statistics value.
cgnp_pair <- sample_correlated_gnp_pair(n = 50, corr = 0.5, p = 0.5)
g1 <- cgnp_pair$graph1
g2 <- cgnp_pair$graph2
seeds <- 1:50 <= 10
match <- gm(g1, g2, seeds, method = "indefinite")
# Application: select best matched seeds from non seeds as new seeds, and do the
# graph matching iteratively to get higher matching accuracy
best_matches(A = g1, B = g2, match = match, measure = "row_perm_stat", num = 5, true_label = 1:50)
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