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Search - DATA CLUSTERING - List
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dataming_3
DL : 0
数据挖掘领域中聚类分析的相关的PPT以及一个聚类算法介绍-field of data mining cluster analysis of the PPT, and a clustering algorithm introduced
Date
: 2025-12-20
Size
: 1.57mb
User
:
qiaoyu
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File Format
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Sequential-clustering-method
DL : 0
水文,变异点的检验,有序聚类法,运行环境:excel中vba。按照文件的样式输入数据,ctrl+F11打开vba环境,点击模块1,再点运行就可以了!-Hydrology, the change point test, sequential clustering method, the runtime environment: excel in the Visual Basic. Input data in accordance with the style of the file, ctrl+ F11 to open vba environment, click on Module 1, and then point to run it!
Date
: 2025-12-20
Size
: 7kb
User
:
小虎
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kmeans_report
DL : 0
数据挖掘kmeans图像聚类实验报告 用 VC 或 Java 实现 k-means 聚类算法, 分别以迭代次数及分配不再发生变化为算法终止条件,用图片(自己选择)作为数据集,比较运行时间(画出时间与像素点的关系曲线图,因此须用多幅像素个数不同的图片进行实验) 提交实验报告与源代码。 -Data mining to achieve the k-means clustering algorithm the kmeans image clustering experiment report with VC or Java, respectively, to the number of iterations and distribution no longer change the termination condition for the algorithm as a data set with a picture (of their choice), compare running time (painting out time and the graph showing the relationship of the pixel point, and is therefore subject to experiment with multiple number of pixels of different pictures) submitted to the lab report with the source code.
Date
: 2025-12-20
Size
: 3.5mb
User
:
周生勇
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Km
DL : 0
In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Voronoi cells. The problem is computationally difficult (NP-hard), however there are efficient heuristic algorithms that are commonly employed and converge quickly to a local optimum. These are usually similar to the expectation-maximization algorithm for mixtures of Gaussian distributions via an iterative refinement approach employed by both algorithms. Additionally, they both use cluster centers to model the data, however k-means clustering tends to find clusters of comparable spatial extent, while the expectation-maximization mechanism allows clusters to have different shapes.
Date
: 2025-12-20
Size
: 1kb
User
:
pongpan
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File Format
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DATA
DL : 0
matlab数据文件,聚类标准测试数据,K均值聚类等经典算法都可以用。mat文件-matlab data files, the standard test data clustering, K-means clustering algorithm can be used such as the classic. mat file
Date
: 2025-12-20
Size
: 112kb
User
:
赵赫
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9552010E202
DL : 0
This paper presents a new cluster validity index for nding a suitable number of fuzzy clusters with crisp and fuzzy data. The new index, called the ECAS-index, contains exponential compactness and separation measures. These measures indicate homogeneity within clusters and heterogeneity between clusters, respectively. Moreover, a fuzzy c-mean algorithm is used for fuzzy clustering with crisp data, and a fuzzy k-numbers clustering is used for clustering with fuzzy data. In comparison to other indices, it is evident that the proposed index is more effective and robust under different conditions of data sets, such as noisy environments and large data sets.
Date
: 2025-12-20
Size
: 3.31mb
User
:
m
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LEACH
DL : 0
LEACH [1] is an autonomous adaptive clustering protocol that distributes the energy load evenly among the sensors in the network using randomization. The nodes organize themselves into local clusters, with one node acting as the local base station or cluster head. In order to not drain the battery of a single sensor randomized rotation of the high-energy cluster head position such that it rotates among the various sensors. Once the cluster head has all the data from the nodes in its cluster, the cluster head node aggregates the data and then transmits the compressed data to the base station. Since it compress the amount of data being sent from the clusters to the base station, energy dissipation is reduced and system lifetime is thus enhanced. A Comparative Analysis of Energy-Efficient Routing Protocols 401 This
Date
: 2025-12-20
Size
: 2kb
User
:
jagadish
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sas_cluster
DL : 0
sas 聚类分析带教程(PPT)含检验数据(clustering analysis band tutorial (PPT) containing test data)
Date
: 2025-12-20
Size
: 6.16mb
User
:
张建357
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