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

机译:一种取向的群集星形坐标转换方法,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:进行聚类过程时,用户通常涉及聚类结果是否足够可靠以反映实际的聚类现象。集群和初始群集中心的数量是两个关键参数,其高度影响聚类结果的可靠性。我们提出了一种面向聚类的星形坐标转换(COSCT)方法,以帮助用户更加自信地确定两个参数。通过COSCT来自多维空间的所有对象都自适应地被转换为2D星坐标平面,使得通过观察平面中的聚类现象,可以容易地进行聚类参数化。为了增强星形坐标平面的簇显示质量,开发了特征加权和坐标排列程序。使用一组实验来证明COSCT方法的有效性。

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