getIs2(bic, dim, nstart = 20, solver = "nn", cpr = FALSE, cpc = TRUE, adjust.dist = FALSE)
TRUE
the ME values used as a distance matrix for the TSP are slightly adjusted by adding a the hamming distance divided by a constant.
This keeps identical cases together (which is only necessary if cpr = FALSE
or cpc =
attr(x, "orders")
.The difference to getIs is that rows and columns which are identical with respect to the biclusters are combined before the optimization. This keeps identical categories together and also speeds up the algorithm considerably (depending on the TSP solver).
The TSP solver solver = "nearest_insertion"
for instance is inefficient in this case since it has to add (identical) cases one by one.