Calculate Euclidean distance of test vector to all training vectors that were sampled.
The in this work applied k-NN algorithm functions as follows: (1) Calculate Euclidean distance of test vector to all training vectors that were sampled.
Based on feature vectors extracted from normal signals, a SVDD model fitting a tight hypersphere around them is trained, the general distance of test data to this hypersphere is used as the health index.
Thus, the higher distance of test sample 1 to the reference set is partly due to a critically low sequence read coverage of regions with an extreme GC-content.
The most direct means of testing this distance is to determine whether the common ancestors of insect and plant clades are contemporaneous or not.
If the average distance of the tested strain to each of the genogroup members is almost equal to the average distance among all strains in a genogroup, the identification factor will approach the value of one.
Segment-length ratio indices are more appropriate than indices of absolute distance when testing predictions of competition hypotheses on size or morphology patterns [52].
The same program was used to run a Mantel test (Mantel 1967), with 10 000 permutations, to estimate the correlation of pairwise linearized distances with a matrix of linear geographic distances to test the hypothesis of genetic isolation by geographic distance (isolation by distance, IBD).
I didn't expect reefs so close to the populous mainland, and within shouting distance of a testing range, to be especially lush, and they weren't, but I did see barracudas, enormous lobsters, fan corals and thousands of tiny iridescent fish.
We applied two different measures of genetic distances to test different assumptions.
