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数据挖掘算法，K-means聚类算法源代码，用于聚类分析-data mining algorithms, K-means clustering algorithm source code for the cluster analysis
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数据挖掘算法，fuzzy-K-means聚类算法源代码，用于模糊聚类分析-data mining algorithms, fuzzy-K-means clustering algorithm source code for Fuzzy Cluster Analysis
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BIRCH (balanced iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm used to perform hierarchical clustering over particularly large data-sets. An advantage of Birch is its ability to incrementally and dynamic
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对应聚类分析与盲矿体的地球化学预测 为利用矿区地球化学数据进行找矿靶区预测，采用了对应的聚类分析方法-Cluster analysis and blind orebodies corresponding geochemical prediction for the use of data mining geochemical prospecting target prediction, using the corresponding cluster analysis method
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K-means算法是最为经典的基于划分的聚类方法，是十大经典数据挖掘算法之一。K-means算法的基本思想是：以空间中k个点为中心进行聚类，对最靠近他们的对象归类。通过迭代的方法，逐次更新各聚类中心的值，直至得到最好的聚类结果。-K-means algorithm is based on the division of the classic clustering method, is ten classic one of data mining algorithm. K-means the
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k-means算法实现，数据挖掘中经常用到的聚类分析算法。是最经典的常用算法。-k-means algorithm, cluster analysis algorithm often used in data mining. Is the most classic of common algorithms.
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数据挖掘中, k-Means 算法是一种 cluster analysis 的算法,其主要是来计算数据聚集的算法,主要通过不断地取离种子点最近均值的算法。-In data mining, k- Means algorithm is a kind of cluster analysis algorithm, the main is to calculate the data aggregation algorithm, mainly through constantly take the seed
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k-means clustering is a method of vector quantization, originally signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the clu
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cluster data using iterative scheme
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K-means聚类算法的matlab实现(k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each obse
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