搜索资源列表
K均值
- 本程序通过k均值算法对两类进行分类。通过任意选择初始点，由k均值很快找到两类的中心点-the procedure k means algorithm to classify two types. Through arbitrary choice initial point, k Mean quickly found two focal point
K均值算法
- 实现K均值算法，读取文件，实现K均值的分类。-K-means algorithm to achieve, reading the paper, K-mean achievement category.
k_mean_binary
- 是对K-mean算法的数据分析处理,运行时需输入数据,其中有参考数据,希望对大家的学习有所帮助-of K-mean algorithm for data analysis, run-time required to input data, including reference materials, we hope to learn some help
KMEANS_FixedBug
- 经典的K均值分类算法源码，修正了原作者没有处理当类中样本为0的情况下的bug-classic K-mean classification algorithm source code, that the original author did not address when the category 0 samples of the bug
MFY_kmeans
- 这是我帮一个本科生做的毕业设计，实现的数据挖掘的k均值和k中心算法，其中包含了我做的两个二维的数据集，感觉要预先知道k的参数值，不是很方便-This is what I do to help an undergraduate graduation Design, Implementation of the Data Mining mean k and k center algorithm, which includes me to do two two-dimensional data sets
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
K-means
- 模式识别 k-mean算法程序，用Visual c++编写-K-mean algorithm for pattern recognition procedures, using Visual c++ Prepared
K-Means
- 这是K-neans动态聚类算法的源程序，是人工智能领域很有用的一种聚类方法。-This is K-neans source dynamic clustering algorithm, the field of artificial intelligence are useful in a clustering method.
K-Means.Algorithm
- 算法，k-mean搜索方法，执行起来很快，推荐。-Algorithm, k-mean search methods, to implement quickly, recommended.
textclusterr
- 文档分类，用K均值，加入了K的选择算法，不用人为设定聚类个数-Document classification, using K-means, joined the K of the selection algorithm, not the number of artificial clustering
K-Means
- K-mean算法实现程序-K-mean algorithm program! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
K_MeansAlgo
- 改进的K-Means算法，通过改进传统K-Means算法，剔除远离中心均值的离散点，加快算法的收敛速度。-Improved K-Means algorithm, by improving the traditional K-Means algorithm, removing the mean of discrete points away from the center to accelerate the convergence speed.
K-means
- 均值为K的聚类算法，是一种对聚类数据进行的最简单的算法，广泛应用在各种场合中。-K mean clustering algorithm for clustering data is the most simple algorithm, widely used in various occasions.
amend1
- 用C语言实现的K均值聚类算法，一共有3个类，并且给出了150个样本点，样本点为四维数据-Those files implements the function of classifying the four dimensional data by using the K-mean algorithm.
K-Mean
- Kmeans 聚类算法的实现 测试， 内部包含 Kmode选项-Implementation of Kmeans cluster algorithm and testing, internal options include Kmode
K-mean
- K平均算法，python编写,性能较好。通用性强-K-means algorithm, python write
kjunzhi
- 利用k均值算法将两个female和male包含身高与体重的100个样本进行类别数为2的聚类-Using the K mean algorithm, 100 female and male were clustered with two samples of height and weight for 2 of the clusters.
K-mean
- 聚类算法中的k-means算法，和k-medoids 肯定是非常相似的。k-medoids 和 k-means 不一样的地方在于中心点的选取，在 k-means 中，我们将中心点取为当前 cluster 中所有数据点的平均值。-Clustering algorithm k-means algorithm, and k-medoids certainly very similar. k-medoids and k-means not the same place that the center o
RBF-k均值聚类
- RBF（径向基神经网络）网络是一种重要的神经网络，RBF网络的训练分为两步，第一步是通过聚类算法得到初始的权值，第二步是根据训练数据训练网络的权值。RBF权值的初始聚类方法较为复杂，比较简单的有K均值聚类，复杂的有遗传聚类，蚁群聚类等，这个RBF网络的程序是基于K均值聚类的RBF代码。(RBF (radial basis function network) is an important neural network. The training of RBF network is divided
k_mean
- K—mean算法的matlab实现，适合算法初学者，可加深对其的理解(Matlab implementation of K - mean algorithm)