搜索资源列表
Algorithm-for-knn-of
- 提出了一种改进的散乱数据点k近邻搜索算法-An improved algorithm for searching points’k nearest neighbor is presented
mpnn_Nearest-neighbor-library
- motion planning strategies for finding the nearest node in the search tree.
Untitled
- 自己编写的对一幅图像实现最近邻插值和双线性插值，可以直接运行，效果很好。-Write your own images of a nearest neighbor interpolation and bilinear interpolation, can be run directly, the effect is very good.
knn
- 模式识别 K近邻法实现，用c实现-K-nearest neighbor method, Pattern Recognition implementation
NearestNeighborMethod
- 最近邻算法，实现。有数据，可以直接运行，并显示效果-Nearest neighbor algorithm.Data can be run directly, and can display
metric-learning_survey_v2
- 关于metric learning的综述，涉及到许多的知识：SVM、kernel、SDP等-This paper surveys the field of distance metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different
points2contour
- 封闭二维图形的最小自由相邻链接 Connect Randomly Ordered 2D Points into a Minimal Nearest-Neighbor Closed Contour-Connect Randomly Ordered 2D Points into a Minimal Nearest-Neighbor Closed Contour
tspsa
- Traveling Salesman Problem (TSP) Nearest Neighbor tour construction
TSP
- Nearest Neighbor for Tsp
K
- 近邻法的基本思想是在测试样本x的k个近邻中，按出现的样本类别来作为x的类别，即先对x的k个近邻一一找出它们的类别，然后对x类别进行判别，即在N个训练样本中，找出x的k个近邻。-The basic idea of the nearest neighbor method in the test sample x k nearest neighbors, according to the type of the sample of x as a category, that is, first k n
MLRE
- MLRE算法，选取最优K近邻，是识别率达到更高-MLRE algorithm select the best K-nearest neighbor, is to achieve a higher recognition rate
FastNN
- 简单快速近邻算法是一种典型的模式识别方法：在二维平面一矩形范围内随机产生训练样本，任意划分为三个区域，用快速近邻法确定待识别实验样本的所属分类。-Simple and fast nearest neighbor algorithm is a typical pattern recognition methods: randomly generated training samples in a rectangular range of two-dimensional plane, arbitra
McCannLowe_CVPR2012_1925
- 图像分类算法，2012年CVPR中的文章，效果还可以，采用“Local Naive Bayes Nearest Neighbor”方法-Image classification algorithm, CVPR 2012 article, the effect can also " Local Naive Bayes Nearest Neighbor method
KClassify
- 使用K近邻法设计分类器，对一组数据进行分类-K-nearest neighbor algorithm to design the classifier, to classify a set of data
lbimproved_2009-12-29
- C语言DTW算法实现,主要功能: 1)快速近邻DTW比较 2)算法稳定 3)节省内存-== Key features == 1) Fast Dynamic Time Warping nearest neighbor cost retrieval. 2) Persistence 3) External-memory: you need only a constant amount of RAM
ANNTest
- 查找二维和三维空间中K最近邻点的算法，在Approximate Nearest Neighbor Searching（ANN）的基础上进行了包装，易于使用。-Find the two-dimensional and three-dimensional space of K nearest neighbor algorithm, Approximate Nearest Neighbor Searching (ANN) based on the packaging.
KNN
- K最近邻C实现，测试通过，可以使用，主要适用于数据库定位方法-K nearest neighbor C implementation, the test passes, you can use, mainly applied to the database location method
chaos
- 使用matlab编写的用wolf法求Lyapunov指数的算法程序 假近邻法(False Nearest NeighborFNN)计算嵌入维的Matlab程序 一类基于奇异值分解的Lyapunov指数计算方法-Matlab program using Matlab prepared wolf method and the Lyapunov exponent of the false nearest neighbor algorithm program (False Nearest Nei
Dynamic-vp-tree
- vp-tree动态索引对于给定成对的距离搜索 搜索相邻…… 该文章为国外文献 以供各位参考-Dynamic vp-tree indexing for n-nearest neighbor search for foreign literature for the reference to the given pairs from the article
ANN_1.1.2(Newest-Vision-2010-1-27)-
- ANN是一个构造数据索引结果的程序，可以实现最近邻、KD树等功能。ANN is designed for data sets that are small enough that the search structure can be stored in main memory (in contrast to approaches from databases that assume that the data resides in secondary storage). Points ar