搜索资源列表
IRIS数据
- IRIS数据 用于聚类方法 主要用于模式识别、图像分割等-IRIS data for clustering method used pattern recognition, image segmentation, etc.
IRIS数据
- IRIS数据 用于聚类方法 主要用于模式识别、图像分割等-IRIS data for clustering method used pattern recognition, image segmentation, etc.
ISODATA.Clustering
- ISODATA聚类实验 模式识别课程实验所用的源程序-ISODATA clustering pattern recognition experimental courses used in the experimental program
cindy
- 用java实现的一种聚类方法, 应用了iris这个非常出名的数据 和glass这个非常出名的数据,很不错的,值得大家看看。-Using java realize a clustering method, applied to this very well-known iris data and the glass of this very well-known data, it is good, it is worth to s
isodata
- C++实现isodata聚类算法,基于IRIS数据,-C++ Achieve ISODATA clustering algorithm, based on IRIS data,
GA_FCM
- 基于遗产算法的FCM算法,且对iris标准数据集聚类,适用初学者。-Algorithm based on the heritage of the FCM algorithm, and clustering of the iris standard data categories, the application of beginners.
KMEANS
- 基于matlab的K均值聚类程序。其中用IRIS数据进行验证,得到了很好的结果。文件中包含了演示后的结果图-Matlab-based K-means clustering procedure. Which use IRIS data verification, have had good results. File contains the results of the demonstration plan
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 cluste
Cluster
- 使用分解聚类算法在IRIS数据上进行聚类分析,IRIS数据是由鸢尾属植物的三种单独的花的测量结果所组成,模式类别数为3,特征维数是4,每类各有50个模式样本,总共有150个样本。-The use of decomposition in the IRIS data clustering algorithm on the cluster analysis, IRIS data are from the iris flower three s
C-means
- 使用c-均值聚类算法在IRIS数据上进行聚类分析,随机选择三个初始聚类中心,经过多次迭代,最终将150个样本分为三类。-Use c-means clustering algorithm in the IRIS data on the cluster analysis, three randomly chosen initial cluster centers, through a series of iterative, 150 sam
subtractive
- subtractive clustering
1
- Iris segmentation using fuzzy clustering and DTCWT
irisfcm
- This illustrates how to use Fuzzy C-Means clustering for Iris dataset.
isodata
- ISODATA聚类算法,内附详细注解,使用了Iris数据集。ISODATA是一种常用的聚类算法之一。-ISODATA clustering algorithm, containing detailed notes, using the Iris data set. ISODATA clustering algorithm is a common one.
JMinHEP-1.0.tar
- clustering iris data java
k-means-and-cure-in-Iris-Data-Set
- 聚类算法实验,采用两种不同类型的聚类算法:基于划分的聚类方法k-means和基于层次的聚类方法CURE,采用的数据集是:Iris Data Set,数据集中共包含150组数据信息。 材料中有详细的说明文档,具体介绍了算法实现的细节,很容易理解-Clustering algorithm experiment, using two different types of clustering algorithm: Partition-ba
iris
- 用自组织特征映射神经网络对Iris数据集进行分类,我用神经网络工具箱编写了个简单的程序,实现iris的分类。-Using self-organizing feature map neural network examples of clustering Iris data set classification, I use neural network toolbox to write a simple program, realize
fcm-test
- 模糊聚类iris标准数据测试。。。采用fcm方法。-Fuzzy clustering iris standard test data
k-means-for-iris
- 利用K均值聚类对鸢尾花样本进行聚类的matlab程序,包含源代码、样本数据、聚类结果(The matlab program of clustering iris samples by K-means clustering, including source code, sample data and clustering results)