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
apcluster
- 使用近邻传播聚类算法提取最优波段，并建立预测模型-Communication with neighbor clustering algorithm to extract the best band, and the establishment of prediction models
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
juleifenxi
- 针对实际问题定义一种相似性测度的阈值，然后按最近邻规则指定某些模式样本属于某一个聚类类别。-Practical problems for the similarity measure to define a threshold value, and then press the nearest neighbor rule to designate certain mode of samples belonged to a particular cluster category.
ordinary_algorithm_for_pattern_recognition
- 使用C语言实现的一些简单模式识别聚类算法，用于简单的二维坐标系点的聚类。有最短距离算法、K均值算法、近邻算法、fcm算法、最大最小距离算法。-Using the C language implementation of some simple pattern recognition clustering algorithm for a simple two-dimensional coordinate system point of clustering. Has the shortest di
nearestneighbouralgorithm
- 模式识别中的最近邻算法用matlab实现，简单易懂，并做了实验，用图像表示聚类结果。-The nearest neighbor algorithm for pattern recognition with matlab implementation, simple to understand, and do the experiment, with images that clustering results.
最近邻聚类算法
- 最近邻聚类算法,本程序利用图示来显示聚类之后的结果，效果直观-NearestNeighbor algorithm
get_NH
- 最近邻聚类算法，是经典的聚类算法，能够很好的实现，相信对大家有帮助-Nearest neighbor clustering algorithm
zuijinlin
- 是一种数据最近邻的c聚类程序，实现效果较好-Is a data of the c nearest neighbor clustering procedure, to achieve better results
nn_rbf_learning
- 使用最近邻聚类在线自适应RBF网络学习算法-the learning of RBF net work using NN
K-mean
- 最近邻分类器是一个用来聚类的算法，可以用来对iris数据进行聚类-k-means is a neanest alogorim
SNN_algorithm
- 实现SNN（共享最近邻聚类）算法，已测试，可用-Achieve SNN (Shared Nearest Neighbor Clustering) algorithm has been tested available
www2
- 一种改进的最近邻聚类算法，能够改进普通的最近邻聚类算法的不足-An improved nearest neighbor clustering algorithm, it is possible to improve the lack of common nearest neighbor clustering algorithm
123
- 该程序实现K-均值聚类算法达到K-均值聚类的功能，与凝聚算法 最近邻聚类算法达到最邻聚类的功能。 -The program implements K- K- means clustering algorithm to achieve functional means clustering, and cohesion algorithm- nearest neighbor clustering algorithm to achieve the most-neighbor clustering.
Spectral_ClusteringNJW
- 谱聚类能够识别任意形状的样本空间且收敛于全局最优解，其基本思想是利用样本数据相似矩阵的进行特征分解后得到的特征向量进行聚类，程序进行了几种不同聚类算法的比较，包括Q矩阵聚类，kmeans聚类，第一特征分量聚类，第二广义特征分量聚类，公用数据生成和近邻矩阵生成(Spectral clustering can distinguish arbitrary sample space and converge to the global optimal solution, the basic idea i
ClusteringAlgorithm
- 包含Kmeans聚类，最大最小聚类，最近邻聚类，层次聚类的C++编程(C++ programming including Kmeans clustering, maximum and minimum clustering, nearest neighbor clustering and hierarchical clustering)
最近邻分类代码
- 在linux 下C语言实现最近邻聚类算法，工程已经使用(near K neighbor cluster)
plot_classifier_comparison
- 基于Pythoon的数值聚类分类算法，基于Python的三维立体点的空间最近邻分类(This example shows the effect of imposing a connectivity graph to capture local structure in the data. The graph is simply the graph of 20 nearest neighbors. Two consequences of imposing a connectivity can b
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