搜索资源列表
NNAF
- 一个聚类算法,最近邻吸收高效聚类方法,可以实现图案的较好分辨- Gathers a kind of algorithm, the most close neighbor absorbs highly effective gathers a kind of method, may realize the design to distinguish well
rstree
- 基于内容的多媒体数据库检索算法： 用于最近邻搜索的R*-tree算法-content-based multimedia database search algorithm : Nearest Neighbor Search for the R *- tree algorithm
srtree
- 基于内容的多媒体数据检索算法SR-Tree，类似于R*-tree和SS-tree的最近邻搜索 -content-based multimedia data retrieval algorithm SR-Tree, similar to the R *- tree and SS-tree search of the nearest neighbor
tsp_tsp
- 中国所有大中城市的TSP问题实现。图形演示。采用最近邻法则-all of China's large and medium-sized cities in the TSP to achieve. Presentation graphics. Neighbors recently adopted rules
Myknn
- 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, or k-nearest neighbor algrithom, is a simple and classical classifier algrithom.
classifier_knn
- 最近邻分类器（KNN）的C＋＋源码，适合模式识别、图像处理开发者用！-nearest neighbor classifier (KNN) of the C + + source code, suitable for pattern recognition, image processing developers use!
KNN(C++)
- 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
NearestRecognation
- 程序实现了.net环境下，C++语言的手写数字识别，程序对手写数据进行了去边框处理，采用最近邻法进行了分类-achieved with the program. Net environment, the C language handwritten numeral recognition, procedures for handwritten data to the frame, using nearest neighbor method of classification
knn_map
- 用得最多的是最近邻，此处上传的是K-近邻，即k＝1。matlab环境下的代码。附有实例。-used most often is the nearest neighbor, here is uploaded K-neighbor, k = 1. Matlab environment code. With examples.
LBTree
- 用VC。NET2005实现优秀的最近邻搜索算法LB-TREE的模拟和图形显示。具有建立优良数据结构和搜索功能-VC.NET2005 achieve outstanding nearest neighbor search algorithm LB-TREE simulation and graphics. With excellent data structure and search functions
Classify_Homework
- 模式识别作业——用平均样本法，平均距离法，最近邻法和K近邻法进行分类-pattern recognition operations -- with the average sample, the average distance, nearest neighbor and K-nearest-neighbor classification
linearandnearest
- 图像插值算法（最近邻域和双线性），很好用。-image interpolation algorithm (recent neighborhood and bilinear), is useful.
NearestNeighbor
- 模式识别问题最近邻算法的matlab实现，简单易懂-nearest neighbor pattern recognition algorithm to achieve the Matlab and easily understood
PRAssign
- 脱机手写体识别Matlab源程序 包括特征提取、bayes分类器、K近邻分类及最近邻分类。 Testscr iptRecognition.m：测试代码 scr iptFeaExtract.m ：特征提取 KNearestEstimate.m ：K近邻估计 NearestEstimate.m : 最近邻估计 BayesTrain.m ：训练bayes分类器 Bayes.m ：测试bayes分类器 CrossValidate.m ：m交叉验证 -Offlin
Code
- 用matlab编写的线性插值，最近邻域插值，和双三次样条插值。-using Matlab prepared by the linear interpolation, the recent neighborhood interpolation and bicubic spline interpolation.
NNP
- 最近点对问题，输入数据生成器自动生成2位点对，输出制定电的最近邻-nearest point of the problem, the input data generator automatically generate two points right, electrical output of the nearest neighbor
moshishibie
- 先用C-均值聚类算法程序，并用下列数据进行聚类分析。在确认编程正确后，采用蔡云龙书的附录B中表1的Iris数据进行聚类。然后使用近邻法的快速算法找出待分样本X（设X样本的4个分量x1=x2=x3=x4=6；子集数l=3）的最近邻节点和3-近邻节点及X与它们之间的距离。-First C-means clustering algorithm procedures and with the following data for cluster analysis. After confirming t
ClassifyHomework
- 模式识别,用平均样本法、平均距离法、最近邻法、K近邻法进行分类。-Pattern recognition, with an average of the sample method, the average distance method, nearest neighbor, K-NN classification.
KNN_demon
- 最近邻法语k近邻法的例子，基于matlab平台，有助于初学者学习。(The recent example of the nearest neighbour approach to French K, based on the MATLAB platform, helps beginners to learn.)
kNN
- K最近邻(k-Nearest Neighbor，KNN)分类算法，是一个理论上比较成熟的方法，也是最简单的机器学习算法之一。该方法的思路是：在特征空间中，如果一个样本附近的k个最近(即特征空间中最邻近)样本的大多数属于某一个类别，则该样本也属于这个类别。(K-nearest neighbor (KNN) classification algorithm is a relatively mature method in theory and one of the simplest machine