搜索资源列表
C++
- 数据挖掘算法源码,有聚类算法、分类算法、神经网络分类算法-Source of data mining algorithms, a clustering algorithm, sorting algorithm, neural network classification algorithm
Workpiecefeatureextraction
- 1、有9个工件图像,要求从本章讲授的特征提取方法中,选择3~5种提取工件特征并给出数字结果;链码为必选方法,给出数字结果和图形显示,做到链码和原图像的双向变换显示。(实验报告中应描述相应的特征提取方法并略述实现过程) 2、设计的界面中要具备功能:任选1个工件作为目标,以上述实现的特征提取方法识别该目标的工件类型(即序号),并显示该判别基准特征的数据。 3、有可能的话试用聚类、训练或其他方法对这些工件进行分类。 -err
yichuanmohusuanfa
- 模糊聚类算法,实现对数据的聚类分析,供大家参考-Fuzzy clustering algorithm, the realization of the cluster analysis of data for the U.S. reference
KmeanCluster
- 数据挖掘中的聚类算法简单实例,实现对数字的聚类分析,可以帮助初学者理解聚类算法-Data mining clustering algorithm simple example of the realization of the cluster analysis of the figures that can help beginners understand the clustering algorithm
Kmeans
- 基于Kmeans算法的图像分割,一般Kmeans是数据挖掘中用来聚类的,本试验利用图像中的灰度值作为Kmeans算法的原始点,进行图像分割-Kmeans algorithm based on image segmentation, data mining in general Kmeans is used to clustering, the trial use of the image gray value as the original algorithm Kmeans spots for
program
- 其中有五个程序,详细地说明了五种基于模糊数据的模糊聚类的方法与实现步骤。其中五种程序分别来自五个权威外文论文-Among them, five procedures, detailed descr iption of five based on fuzzy data fuzzy clustering methods and implementation steps. Five procedures in which the authority of a foreign language from
K_average
- k均值聚类或者成为均值聚类,用于对各个数据进行分类-k-means clustering or a means clustering for the classification of the various data
DBSCAN
- Form1.cs是应用聚类算法DBSCAN (Density-Based Spatical Clustering of Application with Noise)的示例,可以通过两个参数EPS和MinPts调节聚类。 DBSCAN.cs是实现文件,聚类算法的进一步信息请参考“数据挖掘”或者相关书籍 聚类示例数据来自于sxdb.mdb,一个Access数据库-Form1.cs is the application of clustering algorithm DBSCAN (Dens
QVCS-Enterprise2.1.11
- 图像数据的模糊聚类分析,图像识别、图像分割,包含FCM算法。-Image data of the fuzzy cluster analysis, image recognition, image segmentation, including the FCM algorithm.
Collaborativefuzzyclusteringmodel
- 协同模糊聚类建模通过特征选择和协同模糊聚类的模糊建模方法构建T-S模型,并用此模型对数据进行测试。-Collaborative fuzzy clustering modeling and collaboration through the feature selection fuzzy clustering TS fuzzy modeling method to build models and use this model of data for testing.
12358964fcmdemo
- 是遗传聚类的demo,参照自己的数据对程序进行小小的改编即可,使用简单方便。-Are genetic clustering demo, with reference to its own data on the procedure can be little adaptation, the use of easy and convenient.
Ccluster
- 一种基于matlab语言编程实现的数据聚类算法,可以实现数据的快速聚类。-A programming language based on the matlab implementation of the data clustering algorithm, can achieve data clustering Express.
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
weka-src
- Java 编写的多种数据挖掘算法 包括聚类、分类、预处理等-Java to prepare a variety of data mining algorithms, including clustering, classification, preprocessing, etc.
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 separate components of the meas
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 samples will eventually fall into
K_average
- matlab实现的k均值聚类算法,可以实现对大量数据的有效分类-matlab implementation of the k-means clustering algorithm, can achieve a large amount of data on an effective classification
Cmeansalgorithmmatlabprocessprocedures
- C均值法的程序算法matlab 程序,本程序用MATLAB实现了聚类分析的功能,保存tex文件中,无数据-C-means algorithm matlab process procedures, the procedures used MATLAB implementation of the cluster analysis function, preservation of tex file, no data
k-means
- 实现了K均值算法,可以对movielens上的数据进行自动分类,给出推荐值,是数据挖掘中的信息推介必要的算法工具。可以直接对movelens的数据进行聚类-Implementation of the K-means algorithm, can movielens on automatic classification of data, recommend give the value of data mining are to promote the necessary information
KAV
- KAV是利用Visual C++ 6.0编写的一个小程序,能实现对特定数据结果的文本数据进行聚类分析,所使用的聚类方法是K均值。 -KAV is the use of Visual C++ 6.0 to prepare a small procedure to achieve the outcome of specific data on the text data clustering analysis, the use of the K-means clustering method.