搜索资源列表
KMEANS
- C++版本的kmeans算法，可以实现任意维度，任意数量的聚类，输出信息非常完整。-C++ version of the kmeans algorithm can achieve any dimension, any number of clustering, the output information is complete.
KMEANS
- 实现k均值聚类算，输出聚类中心和聚类后的分组结果-To achieve k-means clustering calculation, the output cluster centers and cluster grouping of the results of post-
kmeans
- 这是用C++编写的数据挖掘的聚类算法。算法中使用了链表结构做为存储数据的容器。-It is written in C++, data mining clustering algorithm. Algorithm is used to store data as a linked list structure of the container.
kmeans-in-statistics
- 这是K-means聚类算法的源代码，可实现任意多统计数据的归类处理。代码为原创，用途主要在数理统计方面，而不是常见的图像处理等方面。内附详细的使用说明。-This is the K-means clustering algorithm source code, enabling the classification of any number of statistical data processing. Code for my original, uses mainly in mathemat
FB_DataMing_kmeans
- k-means数据挖掘算法，基于kmeans聚类算法工艺参数基准值的挖掘-mining data mining of the k-means algorithm, based on the kmeans clustering algorithms process parameters reference value
kmeans
- kmeans聚类，用于时间序列无监督聚类-kmeans clustering for unsupervised clustering time series
kmeans
- kmeans methode (k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean)
kmeans
- k_means方法的聚类算法，多维数据可用-clustering algorithm k_means methods, multidimensional data is available
KMeans
- K-均值聚类算法，属于无监督机器学习算法，发现给定数据集的k个簇的算法。 首先，随机确定k个初始点作为质心，然后将数据集中的每个点分配到一个簇中，为每个点找距其最近的质心， 将其分配给该质心对应的簇，更新每一个簇的质心，直到质心不在变化。 K-均值聚类算法一个优点是k是用户自定义的参数，用户并不知道是否好，与此同时，K-均值算法收敛但是聚类效果差， 由于算法收敛到了局部最小值，而非全局最小值。 K-均值聚类算法的一个变形是二分K-均值聚类算法，该算法首先将所有点作为一个簇，然
kmeans-al-math
- C# to achieve k means clustering algorithm, document clustering C# source code, k-means clustering algorithm 29-C# to achieve k means clustering algorithm, document clustering C# source code, k-means clustering algorithm 29111
Kmeans
- 该算法是实现Kmean聚类算法。包含初始聚类中心，聚类成员列表，最终聚类中心，最终聚类中心的距离，方差分析表，每个聚类中的案例数。-The algorithm is a clustering algorithm to achieve Kmean. Contains the initial cluster centers, cluster membership list, the final cluster centers the final cluster centers, ANOVA tab
Kmeans
- 利用java实现了k-means聚类，数据集是由Math.random函数产生的。-K-means clustering was achieved with Java.The data set was created by Math.random.
kmeans-and-DBSCAN
- K_means and DBSCAN algorithm for clustering
kmeans
- c++编写的聚类程序，功能实现：kmeans聚类方法-c++ clustering procedure, function realization: kmeans clustering method
kmeans
- K-means的聚类算法，比较有用的代码，希望对大家有用。-K-means clustering algorithm, more useful code, we hope to be useful.
kMeans
- 用python实现k-means算法。随机生成二位可视化数据集 然后进行可视化聚类(The k-means algorithm is implemented with Python. Randomly generate two bit visual data set and visualize clustering.)