New Algorithms for Efficient High-Dimensional Nonparametric Classification. Ting Liu, Andrew W. Moore, and Alexander Gray. Overview. Introduction k Nearest Neighbors ( k -NN) KNS1: conventional k -NN search New algorithms for k -NN classification KNS2: for skewed-class data
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New Algorithms for Efficient High-Dimensional Nonparametric Classification
Ting Liu, Andrew W. Moore, and Alexander Gray
the k-NN of q in
V and Node
Ciis # of the negative points in V closer than the ith positive neighbor to q.
Step 2 “insert negative” is implemented by the recursive function
(nout, Cout)=NegCount(nin, Cin, Node, jparent, Dists)
(nin, Cin) sumarize interesting negative points for V;
(nout, Cout) sumarize interesting negative points for V and Node;
P is a set of balls from Postree, N consists of balls from Negtree.
Randomly pick 1% negative records and 50% positive records as test (986 points)
Train on the reaming 87372 data points