> Hi all,
> Say I have a matrix A with dimension m x 2 and matrix B with
> dimension n x 2. I would like to find the row in A that is closest to
> the each row in B. Here's an example (using a loop):
>
> set.seed(1)
> A <- matrix(runif(12), 6, 2) # 6 x 2
> B <- matrix(runif(6), 3, 2) # 3 x 2
> m <- vector("numeric", nrow(B))
make the lines below a function of a vector argument and
apply it over the rows of B.
?apply for more info. You'll want to know about apply if
you want to avoid loops (which is a good approach).
> for(j in 1:nrow(B)) {
> d <- (A[, 1] - B[j, 1])^2 + (A[, 2] - B[j, 2])^2
> m[j] <- which.min(d)
> }
>
> All I need is m[]. I would like to accomplish this without using the
> loop if possible, since for my real data n > 140K and m > 1K. I hope
> this makes sense.
Thing is, the above approach requires all data to be in main memory.
i hope this is not a problem.
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