Find K nearest neighbors, starting from a distance matrix
Try to use FastKNN CRAN package (although it is not well documented). It offers k.nearest.neighbors
function where an arbitrary distance matrix can be given. Below you have an example that computes the matrix you need.
# arbitrary datatrain <- matrix(sample(c("a","b","c"),12,replace=TRUE), ncol=2) # n x 2n = dim(train)[1]distMatrix <- matrix(runif(n^2,0,1),ncol=n) # n x n# matrix of neighboursk=3nn = matrix(0,n,k) # n x kfor (i in 1:n) nn[i,] = k.nearest.neighbors(i, distMatrix, k = k)
Notice: You can always check Cran packages list for Ctrl+F='knn' related functions: https://cran.r-project.org/web/packages/available_packages_by_name.html
For the record (I won't mark this as the answer), here is a quick-and-dirty solution. Suppose sd.dist
is the special distance matrix. Suppose k.for.nn
is the number of nearest neighbors.
n = nrow(sd.dist)knn.mat = matrix(0, ncol = k.for.nn, nrow = n)knd.mat = knn.matfor(i in 1:n){ knn.mat[i,] = order(sd.dist[i,])[1:k.for.nn] knd.mat[i,] = sd.dist[i,knn.mat[i,]]}
Now knn.mat
is the matrix with the indices of the k
nearest neighbors in each row, and for convenience knd.mat
stores the corresponding distances.