grid-based clustering algorithms and the density-based clustering algorithms. 这种聚类算法的基本思想是将原始数据空间更改为具有确定 【机器学习】【聚类】 , k-medoids、CLARANS 基于密度的聚类(density-based methods) 思想:不是基于距离,而是基于密度,克服距离算法只能发现“类圆形”的缺点。只要一个区域的点的...
grid-based clusteringClustering in a large data set of high dimensionality has always been a serious challenge in the field of data mining. A good clustering method should provide flexible scalability to the number of dimensions as well as the size of a data set. We have proposed a grid-...
The grid-based technique is used for a multi-dimensional dataset. In this technique, we create a grid structure, and the comparison is performed on grids(also know as cells). The grid-based technique is fast and has low computational complexity.--wiki 基于网格的技术用于多维数据集。在这种技术...
International Journal of Data Mining Modelling & ManagementRenxia Wan, Jingchao Chen, Lixin Wang, and Xiaoke Su. Grid-based clustering over an evolving data stream. International Journal of Data Mining, Modelling and Management, 1(4):393-410, 2009....
In this research paper, we present some of the grid based methods such as CLIQUE (CLustering In QUEst) [2], STING (STatistical INformation Grid) [3], MAFIA (Merging of Adaptive Intervals Approach to Spatial Data Mining) [4], Wave Cluster [5]and O-CLUSTER (Orthogonal partitioning CLUSTERing...
grid-based clusteringhigh dimensional data streamsClustering is an important task in mining the evolving data streams. A lot of data streams are high dimensional in nature. Clustering in the high dimensional data space is a complex problem, which is inherently more complex for data streams. Most ...
A grid-based data clustering method is disclosed. A parameter setting step sets a grid parameter and a threshold parameter. A diving step divides a space having a plurality of data points according to
Abstract Grid-based clustering is particularly appropriate to deal with massive datasets. The principle is to first summarize the dataset with a grid representation, and then to merge grid cells in order to obtain clusters. All previous methods use grids with hyper-rectangular cells. In this paper...
We describe a grid-based approach for enterprise-scale data mining, which is based on leveraging parallel database technology for data storage, and on-demand compute servers for parallelism in the statistical computations. This approach is targeted towards the use of data mining in highly-automated...
Grid based clustering; Density based clustering; DBSCAN; GRIDEN; Data mining; Massive spatial data; Parallel computing; 机译:基于网格的聚类;基于密度的聚类;DBSCAN;GRIDEN;数据挖掘;大空间数据;并行计算; 相似文献 外文文献 中文文献 专利 1. K-DBSCAN: an efficient density-based clustering algorithm...