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[MPI] K-meanCluster DL : 0: How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. -How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
Date : 2025-12-31 Size : 2kb User : yangdi
[MPI] kjunzhijulianC++ DL : 0: c++编写的程序，用K均值聚敛的算法，相当的方便。-c++ preparation procedure, using K-means algorithm amassed a considerable convenience.
Date : 2025-12-31 Size : 29kb User : bqllda
[MPI] k-means DL : 0: k-means MPI implementation for sparse matrixes
Date : 2025-12-31 Size : 10kb User : aaz
[MPI] k-means_mapreduce DL : 0: 这是一个k-means算法在单机上的MapReduce实现-This is a k-means algorithm is implemented on a single machine' s MapReduce
Date : 2025-12-31 Size : 25kb User : 张亮
[MPI] K-mean-clustering-algoritm DL : 0: k均值聚类算法，帮助学习、使用，欢迎下载、-k-means clustering algorithm to help learn, use, welcome to download,
Date : 2025-12-31 Size : 30kb User : 为实
[MPI] test3 DL : 0: K-means聚类算法实现策略源代码实现，可以聚类分析一维数据-K-means source programe
Date : 2025-12-31 Size : 2kb User : 李琳
[MPI] CPPkmeans DL : 0: 用C++汇编语言编写的K均值聚类算法，其中包括输入文件的编写格式-C++ written in assembly language using K-means clustering algorithm, including the preparation of the input file format
Date : 2025-12-31 Size : 3kb User : 彩色的迪子
[MPI] k-means DL : 0: mapreduce实现聚类算法KMeans-mapreduce KMeans
Date : 2025-12-31 Size : 57kb User : peng