Description: Compute nearest neighbours (by Euclidean distance) to a set of points of interest from a set of candidate points.
The points of interest can be specified as either a matrix of points (as columns) or indices into the matrix of candidate points.
Points can be of any (within reason) dimension.
nearestneighbour can be used to search for k nearest neighbours, or neighbours within some distance (or both)
If only 1 neighbour is required for each point of interest, nearestneighbour tests to see whether it would be faster to construct the Delaunay Triangulation (delaunayn) and use dsearchn to lookup the neighbours, and if so, automatically computes the neighbours this way. This means the fastest neighbour lookup method is always used.
- [svm_algorith_matlab] - MATLAB program support vector machine
- [delaunay] - Functions/Classes:
- [nearest_neighbour] - nearest neighbour clustering is an algoi
- [nearestneighbour] - Foreign people to write three-dimensiona
- [KNN] - Rough set a very good code- I hope to pr
- [DynamicDelaunay] - The Delaunay triangulation is one of the
- [netlab] - k-Nearest Neighbour classifer in matlab
- [KNN] - The nearest neighbor algorithm written b
- [OLPP] - In face recognition process, non-linear
- [QuickDelFEX123] - MEX routines that can be a faster altern
File list (Check if you may need any files):
demo
....\html
....\....\nndemo.html
....\....\nndemo.png
....\....\nndemo_01.png
....\....\nndemo_02.png
....\....\nndemo_03.png
....\....\nndemo_04.png
....\nndemo.m
....\timingtest.m
license.txt
nearestneighbour.m
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