搜索资源列表
VCk-means
- VC k-means聚类算法源码。kmeans是一种常用的分割算法,简单而又高效-VC k-means clustering algorithm source code. Kmeans is a common segmentation algorithm, simple and efficient
k-mean
- K-means聚类算法的java实现描述!有详尽的说明,对初学者非常有用!
k均值聚类算法
- k均值算法的源代码-k means algorithm source code
k-meansjava.rar
- 用JAVA语言实现的经典聚类算法k-means,聚类与分类不同,它是无监督的过程,,JAVA language used to achieve a classic clustering algorithm k-means, clustering and classification of different, it is the unsupervised process,
KMeans
- K均值算法,Matlab实现,输入分类数,实现分类-K means algorithm, Matlab implementation, enter the number of classifications to achieve classification
聚类K-Medoids算法
- 聚类K-Medoids算法。文件里面包含了详细的程序说明和示例。-K-Medoids clustering algorithm.The file contains a detailed descr iption of the procedures and examples.
demo
- 实现数据挖掘的几个算法,包括模糊聚类,K均值,以及K近邻等聚类算法-Some of the implementation of data mining algorithms, including fuzzy clustering, K-means, as well as neighbors, such as clustering algorithm K
k-means
- K-means均值聚类算法,用C语言实现 k-均值聚类算法 -Means K-means clustering algorithm, using C language realization of k-means clustering algorithm
k-means
- k-均值聚类算法c语言版用于划分聚类,适合用于数据挖掘之中-k-means clustering algorithm c language version
KMEANS
- K-Mean聚类算法,对各种格式的图像进行分层聚类。-This is a K-Mean culstering aligroam.
k-means(java)
- k-means算法是基于划分的聚类方法,本算法简单,便于理解,以可视化界面的形式将结果展示出来。-k-means clustering algorithm is based on the division method, this algorithm is simple and easy to understand visual interface to the form of the results.
KClustering
- k-聚类算法-k- gathers a kind of algorithm
meanks
- 这个应用程序是使用k均值聚类算法分割一个灰度图像。-This application is to use k-means clustering algorithms partition a gray image.
k-means
- 聚类实现,k-means算法的一个MATLAB实现-Achieve clustering, k-means algorithm to achieve a MATLAB
DBSCAN聚类
- Python密度聚类 最近在Science上的一篇基于密度的聚类算法《Clustering by fast search and find of density peaks》引起了大家的关注(在我的博文“论文中的机器学习算法——基于密度峰值的聚类算法”中也进行了中文的描述)。于是我就想了解下基于密度的聚类算法,熟悉下基于密度的聚类算法与基于距离的聚类算法,如K-Means算法之间的区别。 基于密度的聚类算法主要的目标是寻找被低密度区域分离的高密度区域。与基于距离的聚类算法不同的是,基
K_means
- k-means的实现,基本的计算方式,444(k means asdasdsfsafdsadfas)
K-means
- K-means算法是硬聚类算法,是典型的基于原型的目标函数聚类方法的代表,它是数据点到原型的某种距离作为优化的目标函数,利用函数求极值的方法得到迭代运算的调整规则。K-means算法以欧式距离作为相似度测度,它是求对应某一初始聚类中心向量V最优分类,使得评价指标J最小。算法采用误差平方和准则函数作为聚类准则函数。(The K-means algorithm is a hard clustering algorithm, which is representative of the prototy
IDS
- 利用增强型K-means聚类算法实现入侵检测系统模型的设计(Design of Intrusion Detection System Model Using Enhanced K-means Clustering Algorithms)
ABC-K-means
- 基于改进人工蜂群算法的K均值聚类算法-喻金平-郑杰-梅宏标,matlab(K-means clustering algorithm based on improved artificial bee colony algorithm-Yu Jinping-Zheng Jie-Mei Hongbiao, matlab)
主动半监督K_means聚类算法研究及应用_吕峰.caj
- 基于师生模型实现半监督学习,百万级数据级(Semi supervised learning based on teacher-student model, million data level)