搜索资源列表
K-means
- 在里面的的是一些关于k-means的东西，用的mnist数据(I try the Mnits data and use K-means to doing the clustering)
k均值聚类
- 用VC++写的K均值聚类算法，可以直接使用(K mean clustering algorithm is written by VC++ , which can be used directly.)
k-means-matlab
- 利用k-means算法实现二维平面点的聚类，包括了运行源代码和结果图(The k-means algorithm is used to realize the clustering of two-dimensional plane points, including the running source code and the result graph)
K近邻互信息计算程序
- matlab用于计算K近邻互信息量程序，多变量相关性(K nearest neighbor mutual information computing program)
K线包含处理
- 缠论K线包含处理dll，顶分型和底分型的判断，无笔和线段的编写(Free good stock index source code, although this version is not strong DLL version, but it is also very accurate)
K-means聚类
- K-means聚类程序，可用于聚类问题，自动产生大量数据，生成聚类图片(K-means clustering program, can be used for clustering problems, automatically generate large amounts of data, generate clustering images)
K-means
- K-means的简单实现，期中例子是实现了几组，程序简单，缺陷比较明显(Simple implementation of K-means)
k-means
- 实现k-means聚类算法，里面有数据可以作为测试(This file is use to achieve k-means clustering algorithm.There are data can be used as a test.)
K-SVD_SOMP-master
- 基于K-SVD方法的图像去噪算法，代码是MATLAB版的(Image denoising algorithm based on K-SVD method, the code is MATLAB version of)
k-means-master
- k-means algorithm with matlab test code is very perfect
k-mediod-PAM
- k-medoids with matlab is very strong
K-means&DBSCAN
- python实现K-means聚类算法和DBSCAN算法，都是最简单的聚类(Python implements k-means clustering algorithm and DBSCAN algorithm, which are the simplest clustering)
a path with a distance of K and no loop
- 求无向图任意两个顶点是否存在距离为k且不含回路的路径(Whether any two vertex of an undirected graph has a path with a distance of K and no loop)
3-19有向树独立K
- 要求有向树Ｔ的k个独立顶点组成的集合Ｆ，使cost(F)=∑min w(x)*d(x,u)的值达到最小。与有向树k中值问题类似，把有向树变转成为与之等价的二叉树，设Ｔ的以顶点x为根的子树T(x),其左、右儿子顶点分别为y和z。(A set F that consists of a k independent vertex to a tree T is required to minimize the value of the cost (F) = min w (x) *d (x, U). Sim
c# 读取 大智慧 K线 数据FinData1.0
- c# 读取 大智慧 K线 数据FinData1.0(c# framwork4.0 vs202)
Type-K-Thermocouple-Chart-C
- K TYPE THERMOCOUPLE Chart
k-means
- 实现k均值聚类算法，可以使用彩色图像，通过随机初始化聚类中心，完成聚类(The K-means clustering algorithm can use color images to initialize cluster centers randomly and accomplish clustering.)
K-means图像识别
- 利用K-means对图像进行聚类，识别。您可以设置参数达到更好的识别效果(Using K-means to cluster and identify images.You can set parameters to achieve better recognition results)
K---MEANS
- 随机生成1000个二维坐标点并用K-means算法计算聚类结果(1000 two-dimensional coordinate points are generated randomly and the clustering results are calculated by K-means algorithm)
K线蜡烛图
- 将K线信号输出至图标上 可以帮助初学者学习了解k线的基本知识(put the signal on the patten)