41 lines
1.4 KiB
Mathematica
41 lines
1.4 KiB
Mathematica
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function [neighborDistances] = kNearestNeighbors_no_sort(dataMatrix, queryMatrix, k)
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%--------------------------------------------------------------------------
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% Program to find the k - nearest neighbors (kNN) within a set of points.
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% Distance metric used: Euclidean distance
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%
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% Usage:
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% [neighbors distances] = kNearestNeighbors(dataMatrix, queryMatrix, k);
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% dataMatrix (N x D) - N vectors with dimensionality D (within which we search for the nearest neighbors)
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% queryMatrix (M x D) - M query vectors with dimensionality D
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% k (1 x 1) - Number of nearest neighbors desired
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%
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% Example:
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% a = [1 1; 2 2; 3 2; 4 4; 5 6];
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% b = [1 1; 2 1; 6 2];
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% [neighbors distances] = kNearestNeighbors(a,b,2);
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%
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% Output:
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% neighbors =
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% 1 2
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% 1 2
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% 4 3
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%
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% distances =
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% 0 1.4142
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% 1.0000 1.0000
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% 2.8284 3.0000
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%--------------------------------------------------------------------------
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% neighborIds = zeros(size(queryMatrix,1),k);
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% neighborDistances = neighborIds;
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neighborDistances= zeros(size(queryMatrix,1),k);
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numDataVectors = size(dataMatrix,1);
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numQueryVectors = size(queryMatrix,1);
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for i=1:numQueryVectors,
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neighborDistances = sum((repmat(queryMatrix(i,:),numDataVectors,1)-dataMatrix).^2,2);
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% [sortval sortpos] = sort(dist,'ascend');
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% neighborIds(i,:) = sortpos(1:k);
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% neighborDistances(i,:) = sqrt(sortval(1:k));
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end
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