搜索资源列表
realDBSCAN
- 二维的DBSCAN聚类算法，输入（x,y）数组，搜索半径Eps，密度搜索参数Minpts。输出: Clusters，每一行代表一个簇，形式为簇的对象对应的原数据集的ID-two-dimensional clustering algorithm, the input (x, y) array, search radius Eps. Minpts density search parameters. Output : Clusters, each firm on behalf of a cluste
kmeans
- 聚类算法kmeans，比较简单的聚类算法，通过欧几里德距离确定聚类的标准，对二维的点进行聚类-Clustering algorithm kmeans, relatively simple clustering algorithm, through the Euclidean distance to determine the standard clustering of the points of two-dimensional clustering
gcluto_1_0
- 根据聚类结果自动生成二维聚类图，可以支持现有多种平台。-According to the results of auto-generated two-dimensional clustering dendrogram, you can support the existing multiple platforms.
emalgorithmusedtocluster
- 采用em算法对某个具体的二维数据集进行聚类-Em algorithm using two-dimensional data set to a specific cluster
iosdata(N-dimension)
- ISODATA算法实现由原来二维扩展到任意维样本点得聚类分析，具有很强的应用性，代码中对原理性东西作了详细的注释-ISODATA algorithm extended to any dimension from the original two-dimensional sample points have to cluster analysis, has a strong application, the code of the principle of detailed notes of wh
K-average(N-dimension)
- K均值聚类算法实现有二维的聚类扩展到任意维样本点的聚类，代码中附加了详细的原理性说明，还有相关例子提示，效果不错-K-means clustering algorithm to achieve a two-dimensional clustering extends to any dimension of the cluster sample points, the code attached to the principle of detailed instructions, and tips
K-MEANS-N
- K均值聚类算法实现有二维的聚类扩展到任意维样本点的聚类.-K-means clustering algorithm to achieve a two-dimensional clustering extends to any dimension of the cluster sample points.
k-means
- c++实现k均值源码，实现了k-means的算法，并给出界面显示。实例中通过二维空间中的点进行聚类-c++ k-means algorithm, display the cluster result on the two demension
Desktop
- k均值聚类及自组织映射（SOFM）算法应用 二维模式矢量的分类-k-means clustering and self-organizing map (SOFM) algorithm is applied two-dimensional mode vector classification
MaxMinDistance
- 最大最小聚类算法，代码中对10个二维数据进行了聚类操作-Maximum and minimum clustering algorithm, the code for the 10-dimensional data clustering operation
zuoye
- k均值进行聚类分析，把二维模式矢量分成三、四类，用SOFM算法-K-means clustering analysis, the two-dimensional pattern vector is divided into three or four classes, using SOFM algorithm
Pattern-Recognise
- c均值法聚类 mfc 模式识别 二维坐标聚类 图形化操作界面 -c mean mfc
fan_mp28
- 一些自适应信号处理的算法，实现用SDRAM运行nios，同时用SRAM保存摄像头数据，可实现对二维数据的聚类。- Some adaptive signal processing algorithms, Implemented with SDRAM run nios, while saving camera data SRAM, Can realize the two-dimensional data clustering.
yf064
- 有信道编码，调制，信道估计等，可实现对二维数据的聚类，采用的是脉冲对消法。- Channel coding, modulation, channel estimation, Can realize the two-dimensional data clustering, It uses a pulse of consumer law.
nenghao-V8.4
- 分数阶傅里叶变换计算方面,解耦，恢复原信号，可实现对二维数据的聚类。- Fractional Fourier transform computing, Decoupling, restore the original signal, Can realize the two-dimensional data clustering.
mdwsk
- 可实现对二维数据的聚类，用于特征降维，特征融合，相关分析等,PLS部分最小二乘工具箱。- Can realize the two-dimensional data clustering, For feature reduction, feature fusion, correlation analysis, PLS PLS toolbox.
mun_au55
- 包括AHP，因子分析，回归分析，聚类分析，二维声子晶体FDTD方法计算禁带宽度的例子,详细画出了时域和频域的相关图。- Including AHP, factor analysis, regression analysis, cluster analysis, Dimensional phononic crystals FDTD method calculation examples band gap, Correlation diagram shown in detail the time d
som
- 随机产生5类二维坐标系中的数，使用SOM网络进行无监督聚类，将产生的随机数自动聚成五类，并将结果用图像直接显示出来，生成训练好的网络权值(Five kinds of random numbers in two-dimensional coordinate system are generated randomly, and unsupervised clustering is carried out using SOM network. The random numbers generated
som算法
- 机器学习中的som算法，用来聚类分析的，代码中 :param X: 形状是N*D， 输入样本有N个,每个D维 :param output: (n,m)一个元组，为输出层的形状是一个n*m的二维矩阵 :param iteration:迭代次数 :param batch_size:每次迭代时的样本数量 初始化一个权值矩阵，形状为D*(n*m)，即有n*m权值向量，每个D维