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A Clustering-Oriented Star Coordinate Translation Method for Reliable Clustering Parameterization

机译:面向聚类的星坐标转换方法,实现可靠的聚类参数化

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When conducting a clustering process, users are generally concerned whether the clustering result is reliable enough to reflect the actual clustering phenomenon. The number of clusters and initial cluster centers are two critical parameters that influence the reliability of clustering results highly. We propose a Clustering-Oriented Star Coordinate Translation (COSCT) method to help users determining the two parameters more confidently. Through COSCT all objects from a multi-dimensional space are adaptively translated to a 2D star-coordinate plane, so that the clustering parameterization can be easily conducted by observing the clustering phenomenon in the plane. To enhance the cluster-displaying quality of the star-coordinate plane, the feature weighting and coordinate arrangement procedures are developed. The effectiveness of the COSCT method is demonstrated using a set of experiments.
机译:在进行聚类过程时,用户通常会担心聚类结果是否足够可靠以反映实际的聚类现象。聚类数量和初始聚类中心是两个重要参数,会严重影响聚类结果的可靠性。我们提出了一种面向聚类的星坐标平移(COSCT)方法,以帮助用户更自信地确定这两个参数。通过COSCT,可以将多维空间中的所有对象自适应地平移到2D星坐标平面,从而可以通过观察平面中的聚类现象来轻松地进行聚类参数化。为了提高星形坐标平面的群集显示质量,开发了特征权重和坐标排列程序。使用一组实验证明了COSCT方法的有效性。

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