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[SourceCode] nearestneighbour 算法代码 DL : 0: nearestneighbour 算法代码
Update : 2010-11-09 Size : 37.68kb Publisher : pumpkin8000
[OpenGL program] nearestneighbour DL : 0: 国外人写的三维最近点查找程序，采用该程序可以很快找到距某一点或一组点最近的n个点。-Foreign people to write three-dimensional nearest point search procedure, the use of the program can be quickly found from a point or a group of points, the most recent n points.
Update : 2025-02-17 Size : 29kb Publisher : Liang
[AI-NN-PR] nearestneighbour DL : 0: 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.
Update : 2025-02-17 Size : 30kb Publisher : nadir
[matlab] nearestneighbour DL : 0: searching nearest neighbor in a network
Update : 2025-02-17 Size : 29kb Publisher : Sung
[matlab] NearestNeighbour DL : 0: NEAREST NEIGHBOUR FOR TRAVELLING SALESMAN PROBLEM
Update : 2025-02-17 Size : 20kb Publisher : milagros
[matlab] nearestneighbour DL : 0: this is a source code about k-nearest network
Update : 2025-02-17 Size : 4kb Publisher : Inggi Herani
[Other] nearestneighbour DL : 0: 计算点云一个范围内的临近点，找到近邻点对于一个给定的点。-Point cloud computing a range near the point of finding neighbors point for a given point.
Update : 2025-02-17 Size : 3kb Publisher : good
[Compress-Decompress algrithms] tMiefore DL : 0: tMissing data in large insurance datasets affects the learning and classification accuracies in predictivemodelling. Insurance datasets will continue to increase in size as more variables are added to aid inmanaging client risk and will therefore be even more vulnerable to missing data. This paper proposes ahybrid multi-layered artificial immune system and genetic algorithm for partial imputation of missingdata in datasets with numerous variables. The multi-layered artificial immune system creates and storesantibodies that bind to and annihilate an antigen. The genetic algorithm optimises the learning processof a stimulated antibody. The uation of the imputation is performed using the RIPPER, k-nearestneighbour-tMissing data in large insurance datasets affects the learning and classification accuracies in predictivemodelling. Insurance datasets will continue to increase in size as more variables are added to aid inmanaging client risk and will therefore be even more vulnerable to missing data. This paper proposes ahybrid multi-layered artificial immune system and genetic algorithm for partial imputation of missingdata in datasets with numerous variables. The multi-layered artificial immune system creates and storesantibodies that bind to and annihilate an antigen. The genetic algorithm optimises the learning processof a stimulated antibody. The uation of the imputation is performed using the RIPPER, k-nearestneighbour
Update : 2025-02-17 Size : 1.86mb Publisher : yangs
[Software Engineering] TSPNearestNeighbour DL : 0: solving TSP using NearestNeighbour
Update : 2025-02-17 Size : 1kb Publisher : eng.hosam84
[Other] nearestneighbour DL : 0: nearest neighbor interpolation for working
Update : 2025-02-17 Size : 97kb Publisher : muthanadf