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将维对分和K均值算法分割图像
- 利用聚类算法分割图像,将维对分法只可将图像分为2部分,可以作为二值化的代码,K-均值法可将图像分为任意多部分。程序直接采用R、G、B三色作为特征参数,聚类中心为随机值,当然也可以采用其他参数,程序编译为EXE文件后速度还可以接受,但尚有改进的余地,那位高手有空修改的话,请给我也发份代码。-clustering algorithm using image segmentation, Victoria right method can only image is divided into two p
K-Mean1
- 编写K-均值聚类算法程序,对下图所示数据进行聚类分析(选k=2)-prepare K-means clustering algorithm, the data shown in the chart below cluster analysis (EAC k = 2)
cluster-1.37.tar
- 聚类算法包,包括K-Means,性能好,有例程
kmeansNetlab
- KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorithm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, with each row corresponding to
Cluster
- 一个利用KDD1999数据集而完成的改进K-means聚类算法的实现.
以K-均值聚类结果为初始解的模拟退火聚类
- 由于K-均值聚类算法局部最优的特点,而模拟退火算法理论上具有全局最优的特点。因此,用模拟退火算法对聚类进行了改进。20组聚类仿真表明,平均每次对K结果值改进8次左右,效果显著。下一步工作:实际上在高温区随机生成邻域是个组合爆炸问题(见本人上载软件‘k-均值聚类算法’所述),高温跳出局部解的概率几乎为0,因此正考虑采用凸包约束进行模拟聚类,相关工作正在进行。很快将奉献给各位朋友。-as K-means clustering algorithm for optimal local character
zhong
- 系统聚类算法K-means 属于聚类分析中一种基本的划分方法,常采用误差平方和准则函数作为聚类准则,该算法在处理大数据集时是相对可伸缩且高效率的,同时具有潜在的数据并行性。但是这种算法依赖于初始值的选择以及数据的输入顺序;此外,当运用误差平方和准则函数测度聚类效果时,如果各簇的形状和大小差别很大,为使误差平方和 Jc 值达到最小有可能出现将大的聚类簇分割的现象。-system clustering algorithm K-means cluster analysis is a basic met
kmean
- 使用k-means算法对150个数据集进行分簇。-K-means algorithm using 150 data sets to carry out sub-cluster.
knn
- k最邻近算法,经典的分类算法,绝对有帮助-k-nearest neighbour algorithm,it is a classical algorithm for text cluster
kmeans
- 基于K-means的模糊聚类分析方法,很有用的-Based on the fuzzy K-means cluster analysis, very useful
PhamDN05-kmeans
- k-means cluster algorithm
MatlabFuzzyClusteringAnalysis
- 采用K- means 算法和FCM 算法实现对47 个城市竞争力的聚类分析-Using K-means algorithm and FCM algorithm to achieve the competitiveness of 47 cities in the cluster analysis
colorimagek_means
- 自己根据K-MEANS思想在MATLAB下实现的彩色图像分割算法程序,用最普通的语句实现,通俗易懂。可以直接用于对彩色细胞图像的分割,分割结果比较准确,-K-MEANS in accordance with their own ideas in MATLAB to achieve color image segmentation algorithm based on the procedures used to achieve the most common statement, user-fr
K-means-clustering-algorithm
- K-均值聚类算法。可自由输入初始聚类中心的个数和其坐标。-K- means clustering algorithm. The number can be entered free initial cluster centers and their coordinates.
k-means
- k-means算法的一个小实例,很好的展示了,算法的过程,测试聚类文件在txt中-A small example k-means algorithm, a good showing, the algorithm process, the test cluster file txt
k-means-iris
- 运用k-means算法对IRIS数据集进行聚类分析-K-means algorithm is appliled to do cluster analysis for IRIS dataset.
K-means-clustering-algorithm
- k均值聚类是最著名的划分聚类算法,由于简洁和效率使得他成为所有聚类算法中最广泛使用的。给定一个数据点集合和需要的聚类数目k,k由用户指定,k均值算法根据某个距离函数反复把数据分入k个聚类中。-K-means clustering is one of the most famous partitioning clustering algorithm, due to the simplicity and efficiency makes him become the most widely used
Kmeans
- 机器学习聚类K-means算法,用于无标签数据的聚类(Machine learning clustering K-means algorithm is applied to cluster of unlabeled data.)
cluster
- 聚类的算法,包括K-means,密度聚类,密度比聚类,谱聚类等(Clustering algorithm, including k-means, density clustering, density ratio clustering, spectral clustering, etc)
c+=
- k-means c++, 聚类算法-含代码说明。聚类(Cluster)分析是由若干模式(Pattern)组成的,通常,模式是一个度量(Measurement)的向量,或者是多维空间中的一个点。(k-means c++,Partitioning Methods,Hierarchical Methods,density-based methods,grid-based methods,Model-Based Methods)