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K-Nearest neighbour algorithm-K- Nearest neighbor algorithm
Update : 2025-02-19 Size : 1kb Publisher : shang jie

DL : 0
knn,即k最近邻算法是模式识别中的一种比较简单而经典的分类算法-knn, k-nearest neighbor pattern recognition algorithm is a relatively simple and classic classification algorithm
Update : 2025-02-19 Size : 17kb Publisher : 才华

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k最近邻分类算法:用C++实现KNN分类-k Nearest Neighbor Classification Algorithm: The C++ realize KNN classification
Update : 2025-02-19 Size : 296kb Publisher : 徐晓云

nearest neighbour clustering is an algoithm that puts data in categories. This algotithm is a data mining subject. Similar data is put in the same cluster.
Update : 2025-02-19 Size : 579kb Publisher : Asli Imre

Affine geometric transform combined with Nearest neighbour or trilinear interpolation
Update : 2025-02-19 Size : 1kb Publisher : Durmen

data mining k nearest neighbour
Update : 2025-02-19 Size : 1kb Publisher : said

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k-nearest neighbour classifier source code
Update : 2025-02-19 Size : 1kb Publisher : zeinab

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Classification of Traditional Chinese Medicine by Nearest- Neighbour Classifier and Genetic Algorithm
Update : 2025-02-19 Size : 250kb Publisher : amila banuka

* Zooming and Shrinking Images -(a) Write a computer program capable of zooming and shrinking an image by nearest neighbour and bilinear interpolation. The input to your program is the desired size of the resulting image in the horizontal and vertical direction. Then your program should create and display the resulting image in the desired size. Note: You cannot use the existing functions in the CImg library for zooming and shrinking. (b) Download the image (Fig2.19(a)) of size 512 x 512 and use your program to shrink this image to sizes 256 x 256 pixels, 100 x 100 pixels, and 30 x 30 pixels, using both nearest neighbour and bilinear interpolation. (c) Use your program to zoom each of the resulting images in (b) back to 500 x 500 with their respective interpolation methods. Explain the reasons for their differences from the original attached image.
Update : 2025-02-19 Size : 4.18mb Publisher : k

RBF Regression Nearest Neighbour
Update : 2025-02-19 Size : 141kb Publisher : ling

Multiple-Instance Nearest Neighbour with Distribution learner.
Update : 2025-02-19 Size : 8kb Publisher : MMM

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k最邻近算法,经典的分类算法,绝对有帮助-k-nearest neighbour algorithm,it is a classical algorithm for text cluster
Update : 2025-02-19 Size : 17kb Publisher : freesunshine

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KDnnTree for KD tree construct and search for nearest neighbour
Update : 2025-02-19 Size : 3kb Publisher : peter

FAST K-NEAREST NEIGHBORS SEARCH -FAST K-NEAREST NEIGHBORS SEARCH Description You can find the description at: http://www.advancedmcode.org/gltree.html A Pro Version has been published on: http://www.advancedmcode.org/gltree-pro-version-a-fast-nearest-neighbour-library-for-matlab-and-c.html Acknowledgements The author wishes to acknowledge the following in the creation of this submission: K-NEAREST NEIGHBOURS AND RADIUS (RANGE) SEARCH This submission has inspired the following: K-NEAREST NEIGHBOURS AND RADIUS (RANGE) SEARCH, FAST K-NEAREST NEIGHBOURS SEARCH 3D VERSION MATLAB release MATLAB 7.5 (R2007b) Other requirements Need a mex compiler Zip File Content Other Files BuildGLTree2DFEX.cpp, BuildGLTree2DFEX.m, DeleteGLTree2DFEX.cpp, DeleteGLTree2DFEX.m, GLTree2DFEX.cpp, GLTree2DFEX.h, license.txt, NNSearch2DFEX.cpp, NNSearch2DFEX.m, TestMexFiles.m
Update : 2025-02-19 Size : 8kb Publisher : 谢冉

k-Nearest Neighbour classifer in matlab
Update : 2025-02-19 Size : 707kb Publisher : 王世涛

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自己的模式识别的作业,matlab实现k近邻算法。-K-Nearest Neighbour algorithm
Update : 2025-02-19 Size : 1kb Publisher : chris

k-近邻算法 m文件 及其excel示范-this package invulved a m-file example of k-nearest neighbour and its corresponding excel file
Update : 2025-02-19 Size : 38kb Publisher : guoguozhong

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This function calculates corrected false nearest neighbour. -This function calculates corrected false nearest neighbour.
Update : 2025-02-19 Size : 1kb Publisher : yanggyimin

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 : 2025-02-19 Size : 30kb Publisher : nadir

采用快速K近邻与Kmeans聚类算法来计算前K个近邻,舍弃了一部分不可能成为待测样本的前K个近邻的训练样本,从而减少了计算量,提高了分类速度-Fast K-nearest neighbor Kmeans clustering algorithm to calculate the K nearest neighbors, abandoning the training samples of the part can not become the first K neighbors of the test sample, thereby reducing the amount of calculation and improve the speed of classification
Update : 2025-02-19 Size : 4kb Publisher : houying
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