搜索资源列表
kmeans-plusPlus
- K-means++算法实现，加强了初始聚类点的选取（careful seeding）-K-means++ algorithm to enhance the selection of the initial clustering points (careful seeding)
spatial_pyramid_code
- 金字塔匹配算法，包括SIFT特征点的提取，聚类和构造金字塔特征表示，论文参考：Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories matlab代码
fcm
- 介绍几种模糊c均值聚类算法，利用该算法进行点云以及图像的分割。-fuzzy c means clustering
aaa
- 本次的算法是相位周期展开聚类，读取256个点 根据拉格朗日插值分数维延时的信号，然后在频率点上展开读取，根据2pi延长相位计算时延！-The cycle phase of the algorithm is to start clustering, read the 256-point Lagrange interpolation based on fractal dimension of the signal delay, and then started to read the frequen
K_Mean
- K均值KMean聚类算法，详细使用方法见cpp文件注释，输入数据格式：点，如 1 空格 1 回车 2 空格 2 。。。 -K-means clustering algorithm KMean detail see cpp files to use notes, input data formats: point, such as 1 Enter 2 spaces 1 space 2. . .
ISODATA
- 一个简单的isodata动态聚类算法isodata，最后可以显示出迭代的结果，包括中心点，方差，样本归类等-A simple ISODATA dynamic clustering algorithm isodata, the last iteration can show results, including the center, variance, sample classification, etc.
jj
- 将150个四维微量数据按聚类分成三类,并找出每一个聚类的中心点-To 150 four-dimensional micro-data are divided into three categories according to cluster and identify the center of each cluster
ppt
- 使用禁忌算法确定聚类簇数目的ppt，该论文改进了聚类算法需事先知道聚类簇中心点的缺点，减少了依赖性-The use of taboo clustering algorithm to determine the number of clusters ppt, the paper has improved clustering algorithm need to know in advance that the shortcomings of clustering cluster center, a
matlab_MRF
- k-均值算法的源码很有用，希望有帮助，请多多指点-k-means algorithm is useful source of hope that has helped, please instruct it
HoughTrans
- Hough变换的实质是将图像空间内具有一定关系的像元进行聚类，寻找能把这些像元用某一解析形式联系起来的参数空间累积对应点。在参数空间不超过二维的情况下， 这种变换有着理想的效果。但是，一旦参数空间增大，计算量便会急剧上升，同时耗费巨大的存储空间，耗时也随之猛增。就此，多年来国内外众多学者针对具体情况对常规Hough变换进行了多方面的探索，并提出了许多有价值的改进方法。-Hough transform is essentially the image space has a certain rel
kmean
- c#下实现图像颜色k均值聚类 将像素点颜色分类并合并-c# implementation of color image k-means clustering to classification of color pixels and merge
selfAffinity
- AP是在数据点的相似度矩阵的基础上进行聚类.对于规模很大的数据集,AP算法是一种快速、有效的聚类方法,这是其他传统的聚类算法所不能及的,-A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this paper. AP takes as input measures of similarity between pairs of data points. AP
123
- 基于Hough 变换的SAR 图像舰船尾迹检测方法。该文引进了K均值聚类方法,将这些点集归类,归类后的每一类的类心能很好的代表一条尾迹,实验结果表明方法是有效的。-Hough transform based on SAR images of ship wake detection. The introduction of the K-means clustering method to classify these points, is classified in each category a
Java
- 数据挖掘 统计学习 分类聚类离散点分布插件小程序-Statistical learning data mining classification clustering distribution of discrete points applet plug-ins
example-template
- K-means聚类算法的实现，可以实现对图像色彩块进行分类，是一个不错的算法，就是处理起来慢了点-K-means clustering algorithm can be achieved color image block classification algorithm is a good means to deal with the point of slow
weka-src
- weka源代码 最全最新的 数据挖掘用机器学习实现。包含聚类 分类 关联规则 离群点监测。java平台-weka most up-to-date source of data mining using machine learning to achieve. Clustering association rules classification contains outliers monitoring. java platform
Autoclust.pdf.tar
- 这就是点集自动聚类的算法，基于delaunay三角剖分。-This is the point set automatic clustering algorithm, based on the delaunay triangulation.
cluster_by_distances
- 通过欧几里德距离对三维空间内的数据点进行聚类： 从文件读入三列表示坐标的数据进行聚类。按项目总数和组数平均划分。首先计算两两之间的距离，选出最近的两个点，再按距离由小到大排序，找出距这两个点最近的若干个点。 除去这些点后对其余的点重复进行上述操作。-By Euclidean distance on three-dimensional space, clustering of data points: from the file read into the three coordinate
xuzhuol
- 基于改进K-means的压缩IP 由于k-means本身受异常点影响较大，这里采用迭代k-means的方法，降低异常点的影响，减少计算量和提高聚类数目的灵活性。并添加合并异常聚类方法，提高聚类的均匀性-K-means based on improved compression IP As k-means itself is influenced by outliers, where an iterative k-means method to reduce the impact of o
k_means
- 聚类分析算法,用来对点的数据集合进行聚类分析-clustering analysis algorithm