nearestneighbour computes nearest neighbours to a set of points from a set of candidate points by Euclidean distance.
Classifiers: Nearest neighbor
- f(x) = label of the training example nearest to x
- All we need is a distance function for our inputs
- No training required!
The 1-N-N classiﬁer is one of the oldest methods known.
The idea: to classify X ﬁnd its closest neighbor among the training points (call it X) and assign to X the label of X
vl_kdtreequery supports two important operations: approximate nearest-neighbor search and k-nearest neighbor search (return the k nearest neighbors to a given query point
[index, distance] = vl_kdtreequery(kdtree, X, Q, 'NumNeighbors', 10, 'MaxComparisons', 15); The
MaxComparisonsoption specifies how many paths in the best-bin-first search of the kd-tree can be checked before giving up and returning the closest point encountered so far. does not compare any point in
Qwith more than 15 points in