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A New Inverse N Gravitation Based Clustering Method for Data Classification

机译:一种新的基于反重力的聚类数据分类方法

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Data classification is one of the core technologies in the field of pattern recognition and machine learning, which is of great theoretical significance and application value. With the increasing improvement of data acquisition, storage, transmission means and the amount of data, how to extract the essential attribute data from massive data, data accurate classification has become an important research topic. Inverse n~(th) n order gravitational field is essentially a generalization of the n order in the physics, which can effectively describe the interaction between all the particles in the gravitational field. This paper proposes a new inverse n~(th) power gravitation (I-n-PG) based clustering method is proposed for data classification. Some randomly generated data samples as well as some well-known classification data sets are used for the verification of the proposed I-n-PG classifier. The experiments show that our proposed I-n-PG classifier performs very well on both of these two test sets.
机译:数据分类是模式识别和机器学习领域的核心技术之一,其理论意义和应用价值具有很大的理论意义和应用价值。随着数据采集,存储,传输装置和数据量的提高,如何从大规模数据中提取基本属性数据,数据准确分类已成为一个重要的研究主题。逆N〜(th)n命令重力场基本上是物理学中N个顺序的推广,其可以有效地描述引力场中所有颗粒之间的相互作用。本文提出了一种新的逆n〜(Th)功率重力(基于I-N-PG)的集群方法,用于数据分类。一些随机生成的数据样本以及一些众所周知的分类数据集用于验证所提出的I-N-PG分类器。实验表明,我们所提出的I-N-PG分类器在这两个测试集中执行非常好。

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