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K-MEANS算法实现
- K-MEANS算法实现
改进的K-Means算法实现车牌字符的分割
- 本实验基于K-Means聚类算法思想实现了字符分割，因为车牌规定是7位的，所以K取7。另外本实验对K-Means算法进行了改进，充分考虑了初始点的设置及迭代结束条件。实验结果证明这种改进的K-Means算法实现车牌字符分割是快速、有效的。
k-MEANS算法
- K-means算法 机器学习
K-Means.rar
- K—means算法简单应用，适合初学者自学。内有中文解释，简单易懂。,K-means algorithm is simple application, suitable for beginners and self-learning. There are Chinese explanation, easy-to-read.
K-means
- 针对一维数据集K-means算法的实现， 针对一维数据集K-means算法的实现， 针对一维数据集K-means算法的实现。-k-means
k-means
- java实现的k-means算法，具有可视化界面，可以作为数据挖掘的作业处理。-java implementation of the k-means algorithm with a visual interface that can handle a data mining operation.
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.
K-means
- 简单实用的k均值聚类算法，可以实现多位向量的简单聚类-Simple and practical k-means clustering algorithm, can achieve more than a simple vector clustering
k-means
- 关于数据挖掘中k-means算法的英文介绍分析-Data Mining on the k-means algorithm analysis in English, introduced
K-means
- k-means算法的实现，实用matlab是实现的，可以用啦做聚类分析-k-means algorithm for the realization of the practical realization of matlab, so you can use cluster analysis
k-means_Program
- k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。 -k-means algorithm to accept input k then n-k of data objects into a cluster in order to make the cluster available to meet: t
K-means
- k-means 算法 step1 初始化K个质心 step2 将所有的点分配给最近的质心 step3 更新质心 step4 若质心都没用变化,则停止,否则返回step2 -k-means algorithm is initialized step1 step2 K a center of mass of all the points assigned to the nearest centroid centroid step3 step4 update no us
GA-k-means
- GA-k-means算法 基于遗传算法的k_means聚类方法的研究(33-48)-GA-k-means algorithm
k-means
- K-means算法是最为经典的基于划分的聚类方法，是十大经典数据挖掘算法之一。K-means算法的基本思想是：以空间中k个点为中心进行聚类，对最靠近他们的对象归类。通过迭代的方法，逐次更新各聚类中心的值，直至得到最好的聚类结果。-K-means algorithm is based on the division of the classic clustering method, is ten classic one of data mining algorithm. K-means the
K-Means PCA降维
- K-Means算法,不要求建立模型之后对结果进行新的预测，没有相应的标签，只是根据数据的特征对数据进行聚类。主成分分析降维对数据进行可视化操作,对features进行降维.(K-Means algorithm does not require the establishment of the model after the new prediction of the results, there is no corresponding tag, but only on the character
k-means
- 此种k-means 算法可以快速的对随机产生的随机数据，进行分类，而且分类的效果比较好，效果直观。(This kind of k-means algorithm can quickly classify randomly generated random data and classify it, and the classification effect is better and the effect is intuitive.)
1、K-means学习
- K-means算法MATLAB仿真，利用一副图像作为数据实现K聚类算法仿真(K-means algorithm, MATLAB simulation)
K-means
- 使用k-means算法对图像进行分割，并利用遗传算法对k-means算法加以改进(The k-means algorithm is used for the segment of images, and the genetic algorithm is used to improve the k-means algorithm)
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---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)