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首页> 外文会议>Transactions on computational collective intelligence XV >Coupled K-Nearest Centroid Classification for Non-iid Data
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Coupled K-Nearest Centroid Classification for Non-iid Data

机译：非id数据的耦合K最近质心分类

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摘要

Most traditional classification methods assume the independence and identical distribution (iid) of objects, attributes and values. However, real world data, such as multi-agent data and behavioral data, usually contains strong couplings among values, attributes and objects, which greatly challenges existing methods and tools. This work targets the coupling similarities from these three perspectives and designs a novel classification method that applies a weighted K-Nearest Centroid to obtain the coupled similarity for non-iid data. Prom value and attribute perspectives, coupled similarity serves as a metric for nominal objects, which consider not only intra-coupled similarity within an attribute but also inter-coupled similarity between attributes. Prom the object perspective, we propose a more effective method that measures the centroid object by connecting all related objects. Extensive experiments on UCI and student data sets reveal that the proposed method outperforms classical methods for higher accuracy, especially in imbalanced data.
机译：大多数传统分类方法都假定对象，属性和值的独立性和相同分布（iid）。但是，现实世界的数据（例如多主体数据和行为数据）通常包含值，属性和对象之间的强耦合，这极大地挑战了现有方法和工具。这项工作从这三个角度针对耦合相似性，并设计了一种新颖的分类方法，该方法应用加权的K最近质心来获得非id数据的耦合相似性。舞会价值和属性角度，耦合相似度是名义对象的度量，不仅考虑属性内的内部耦合相似度，还考虑属性之间的内部耦合相似度。从对象角度出发，我们提出了一种更有效的方法，该方法通过连接所有相关对象来测量质心对象。在UCI和学生数据集上进行的大量实验表明，所提出的方法在精度更高的情况下优于传统方法，尤其是在数据不平衡的情况下。

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  • 来源
  • 会议地点 Salamanca(ES)
  • 作者

    Mu Li; Jinjiu Li; Yuming Ou; Ya Zhang; Dan Luo; Maninder Bahtia; Longbing Cao;

  • 作者单位

    Advanced Analytics Institute, University of Technology Sydney, Ultimo, Australia;

    Advanced Analytics Institute, University of Technology Sydney, Ultimo, Australia;

    Advanced Analytics Institute, University of Technology Sydney, Ultimo, Australia;

    Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China;

    Advanced Analytics Institute, University of Technology Sydney, Ultimo, Australia;

    Australian Tax Office, Sydney, Australia;

    Advanced Analytics Institute, University of Technology Sydney, Ultimo, Australia;

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  • 正文语种 eng
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