搜索资源列表
TestJavaSKNN
- 一个基于网格和最近邻居的聚类算法 Similarity(x, y) = size ( SKNN(x) SKNN(y) )，while Link(x, y)=1-a Grid-based, and the nearest neighbor clustering algorithm similarity (x, y) = size (SKNN (x) SKNN (y)), while Link (x, y) = 1
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
Determining_embedding_dimension_for_phase-space_re
- 假近邻方法(False Nearest Neighbor,FNN)求混沌时间序列重构嵌入维-false neighbor approach (False Nearest Neighbor, FNN) for chaotic time series embedding dimension Reconstruction
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
knn_demo
- K近邻法的matlab程序，发现大家都在找它！-K-nearest neighbor method of Matlab procedures, I found that we all have to find it!
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
kmedfilter
- K近邻中值（均值）滤波器 1) 以待处理像素为中心，作一个m*m的作用模板。 2） 在模板中，选择K个与待处理像素的灰度差为最小的像素。 3） 将这K个像素的灰度均值（中值）替换掉原来的像素值。 -K-nearest neighbor median (mean) a filter) for the pixel to be addressed, for a m * m role template. 2) In the template, select and K-pending p
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
knn
- 在visual basic环境下，实现k-nearest neighbor算法。-in visual basic environment, achieving k-nearest neighbor algorithm.
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
NN3
- 主要是KNN（the k-nearest neighbor algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface mapping）算法。 and a simple clustering algorithm.
knn
- 朴素贝叶斯(Naive Bayes, NB)算法是机器学习领域中常用的一种基于概率的分类算法，非常简单有效。k近邻法(k-Nearest Neighbor, kNN)[30,31]又称为基于实例(Example-based, Instance-bases)的算法，其基本思想相当直观：Rocchio法来源于信息检索系统，后来最早由Hull在1994年应用于分类[74]，从那以后，Rocchio方法就在文本分类中广泛应用起来。
LearningPatternClassificationASurvey
- 模式识别学习综述.该论文的英文参考文献为303篇.很有可读价值.Abstract— Classical and recent results in statistical pattern recognition and learning theory are reviewed in a two-class pattern classification setting. This basic model best illustrates intuition and analysis t
ann
- ANN is a library written in the C++ programming language to support both exact and approximate nearest neighbor searching in spaces of various dimensions. 可以直接用于工程 支持 Kd tree，BBF(best bin first)
events
- * acousticfeatures.m: Matlab scr ipt to generate training and testing files from event timeseries. * afm_mlpatterngen.m: Matlab scr ipt to extract feature information from acoustic event timeseries. * extractevents.m: Matlab scr ipt to extract ev
ann_1.1.1
- The approximate nearest neighbor search code is contained in this zip file. You can use the data contained in to see how the program works.
cluster-2.9
- ClustanGraphics聚类分析工具。提供了11种聚类算法。 Single Linkage (or Minimum Method, Nearest Neighbor) Complete Linkage (or Maximum Method, Furthest Neighbor) Average Linkage (UPGMA) Weighted Average Linkage (WPGMA) Mean Proximity Centroid (UPGMC)