搜索资源列表
K_means
- 自适应Kmeans算法，可直接运行看结果(Adaptive Kmeans algorithm, which can run directly to see the results)
k_means
- MATLAB编写K-means算法，已通过验证，并且已经做成函数，可以直接使用(MATLAB writes the K-means algorithm, which has been verified, and has been made into a function that can be used directly)
K_means
- k-means的实现，基本的计算方式，444(k means asdasdsfsafdsadfas)
K_means
- 本代码可以根据类的初始中心位置和初始点总数，返回每个类的中心位置以及属于哪一类。(This code can return to the central position of each class and what class it belongs to, based on the initial center location and the total number of initial points of the class.)
k_means
- 主成分分析（Principal Component Analysis，PCA）， 是一种统计方法。通过正交变换将一组可能存在相关性的变量转换为一组线性不相关的变量，转换后的这组变量叫主成分。(It is a statistical method. Through orthogonal transformation, a set of variables that can be correlated can be transformed into a group of linearly irrel
Python
- 简单的k_means算法Python 和 MATLAB实现(Simple k_means algorithm Python and MATLAB implementation)
IDL for k_means
- 自己用IDL编写的k-means影像分类程序，已调试，可以直接使用。(Using IDL to write K-means image classification program, has been debugged, can be used directly.)
K_means
- Kmeans实现聚类分析，还有一个用模拟退火优化的Kmeans。(Kmeans implements clustering analysis.)
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)
k_means
- 利用K均值算法对Iris数据集进行聚类，实现Iris数据集的无监督学习。(K-means algorithm is used to cluster iris data set to realize unsupervised learning.)
K_means分类算法
- k-means分类算法MATLAB实现，将数据分类到不同中心范围