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Linear separability and classification complexity

delete2012-07-01
delete14
PRE
AI
D
David Elizondo *
M
Matías Gámez
N
Noelia García
E
Esteban Alfaro
DOI：10.1016/j.eswa.2012.01.090delete
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摘要

摘要

En 中文
我们研究了线性可分性与分类数据集复杂程度之间的关系。线性可分离的分类问题通常比非线性可分离的分类问题更容易解决。这表明线性可分性和分类复杂性之间存在很强的相关性。我们提出了一种新颖而简单的方法来量化分类问题的复杂性。下面所示的方法将任何两类分类问题简化为一系列线性可分离的步骤。这样的减少步骤的数量可以被视为测量不可分离性的程度，并且因此测量问题的复杂性。这种量化又可用作分类数据集的复杂性的度量。提供了使用几个基准获得的结果。（C）2012 Elsevier Ltd.版权所有。
Keyword:
Linear separability
Complexity
Classification
Non linear separability
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期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
2.9W
被引数:
10.2W

机构

D
de montfort university
学者数:
2.3K
论文数: 2.7K
被引数: 0
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