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Kernel Discriminant Analysis and information complexity: advanced models for micro-data mining and micro-marketing solutions

机译:内核判别分析和信息复杂性:用于微数据挖掘和微营销解决方案的高级模型

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摘要

In this paper we shall consider Kernel Discriminant Analysis as an innovative tool for supervised classification in a business vision as a marketing solution. The main idea we propose is the combined use of information complexity and bootstrap process which allows the user to overcome the open problems of such a technique as the kernel function choice and at the same time check the robustness of the rule found.
机译:在本文中,我们将内核判别分析视为一种创新工具,用于将商业愿景作为营销解决方案进行监督分类。我们提出的主要思想是结合使用信息复杂性和引导过程,该过程允许用户克服诸如内核函数选择之类的技术的开放性问题,同时检查所发现规则的鲁棒性。

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