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多李群覆盖学习优化算法
引用本文:吴鲁辉,李凡长,张莉.多李群覆盖学习优化算法[J].计算机科学,2018,45(1):108-112.
作者姓名:吴鲁辉  李凡长  张莉
作者单位:苏州大学计算机科学与技术学院 江苏 苏州215000,苏州大学计算机科学与技术学院 江苏 苏州215000,苏州大学计算机科学与技术学院 江苏 苏州215000
摘    要:目前,已针对李群多连通空间上的道路交叉问题提出了多李群核覆盖学习算法,降低了道路交叉情况,使得分类正确率有了显著提高。但是,核学习算法的性能依赖于核函数的选择。考虑利用李群同态映射将原始李群样本映射到目标李群空间中,使在目标李群空间中不同单连通空间上的道路的关联度最小化,同一单连通空间上的道路的关联度最大化,从而减少道路交叉问题。

关 键 词:李群  覆盖学习  道路交叉  核学习算法
收稿时间:2017/3/3 0:00:00
修稿时间:2017/5/23 0:00:00

Optimization Algorithm of Multiply Lie Group Covering Learning Algorithm
WU Lu-hui,LI Fan-zhang and ZHANG Li.Optimization Algorithm of Multiply Lie Group Covering Learning Algorithm[J].Computer Science,2018,45(1):108-112.
Authors:WU Lu-hui  LI Fan-zhang and ZHANG Li
Affiliation:College of Computer Science and Technology,Soochow University,Suzhou,Jiangsu 215000,China,College of Computer Science and Technology,Soochow University,Suzhou,Jiangsu 215000,China and College of Computer Science and Technology,Soochow University,Suzhou,Jiangsu 215000,China
Abstract:In the previous study,a multiply Lie group kernel covering learning algorithm was proposed to reduce the intersection of roads and improve the correctness of classification for multi-connected spaces.However,the performance of the kernel learning algorithm depends on the choice of kernel function.In this paper,it is considered that the original Lie group samples are mapped to the target Lie group space by the Lie group homomorphic mapping,the degree of the road association is minimized in different single connected spaces in the target Lie group space,and the correlation degree of the road in the same single connected space is maximized,in order to reduce road cross problems.
Keywords:Lie group  Covering learning algorithm  Road cross  Kernel learning algorithm
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