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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:微数据挖掘和微营销解决方案的先进模型

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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,我们将考虑内核判别分析作为作为营销解决方案的商业愿景中监督分类的创新工具。我们提出的主要思想是汇总信息复杂性和引导过程,该过程允许用户克服这种技术的开放问题作为内核功能选择,同时检查找到的规则的稳健性。

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