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数据挖掘，多种聚类算法.FCM, HCM, SVM, 等各种柔性聚类方法。-Data mining, a variety of clustering algorithms. FCM, HCM, SVM, such as flexible clustering method.
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数据挖掘相关算法集合，有聚类、神经网络、遗传算法等的代码实现-Data mining correlation algorithm collection has clustering, neural networks, genetic algorithms, such as the code implementation
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模糊分类是目前比较流行的用于数据挖掘的分类算法，而Fanny是其中一种基于FCM算法,用于实现模糊分类的应用程序-Fuzzy clustering is a popular method for data clustering and classification in data mining, Fanny program realizes one of FCM algorithms, to achieve the application of fuzzy clustering
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data mining agglomerative clustering
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Entropy Based Subspace Clustering for Mining Data - ENCLUS - a new version of PROCLUS algorithm for clustering high dimensional data set.-Entropy Based Subspace Clustering for Mining Data- ENCLUS- a new version of PROCLUS algorithm for clustering hi
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上数据挖掘课的课件，是EM算法的，其中还包括最大似然值，最大似然估计，以及cluster-data mining,EM Algorithm ,Likelihood, Mixture Models and Clustering
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这是用C++编写的数据挖掘的聚类算法。算法中使用了链表结构做为存储数据的容器。-It is written in C++, data mining clustering algorithm. Algorithm is used to store data as a linked list structure of the container.
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k-means数据挖掘算法，基于kmeans聚类算法工艺参数基准值的挖掘-mining data mining of the k-means algorithm, based on the kmeans clustering algorithms process parameters reference value
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KMEAN C#
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 sp
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模糊聚类分析作为无监督机器学习的主要技术之一，是用模糊理论对重要数据分析和建模的方法，建立了样本类属的不确定性描述，能比较客观地反映现实世界，它已经有效地应用在大规模数据分析、数据挖掘、矢量量化、图像分割、模式识别等领域，具有重要的理论与实际应用价值，随着应用的深入发展，模糊聚类算法的研究不断丰富-Unsupervised fuzzy clustering analysis as the main machine learning techniques is the use of fuzzy t
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