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A Reconcile of Density Based and Hierarchical Clustering Based on the Laws of Physics

机译:基于物理定律的基于密度和分层聚类的协调

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In this paper a new approach toward data processing is proposed that is inspired by all the prominent data clustering algorithms proposed by scholars. The main motif that drove this approach was to mix hierarchical clustering methods with Gaussian Estimators as to find a hidden structure in data that was not reachable using traditional bandwidth estimators. Instead the criteria for assessing similarity among data was the principles for Newtonian Physics.
机译:在本文中,提出了一种新的数据处理方法,它受到学者提出的所有突出数据聚类算法的启发。驱动此方法的主要主题是将分层聚类方法与高斯估计器混合,以便在使用传统带宽估算器中找到数据中无法访问的数据中的隐藏结构。而是评估数据相似性的标准是牛顿物理学的原则。

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