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Data analysis computer system and method for conversion of predictive models to equivalent ones

机译:用于将预测模型转换为等效模型的数据分析计算机系统和方法

摘要

The present invention addresses two ubiquitous and pressing problems of modern data analytics technology. Many modern pattern recognition technologies produce models with excellent predictivity but (a) they are “black boxes”, that is they are opaque to the user; (b) they are too large, and/or expensive to execute in less powerful computing platforms. The invention “opens up” a black box model by converting it to a compact and understandable model that is functionally equivalent. The invention also converts a predictive model into a functionally equivalent model into a form that can be implemented and deployed more easily or efficiently in practice. The benefits include: model understandability and defensibility of modeling. A particularly interesting application is that of understanding the decision making of humans, comparison of the behavior of a human or computerized decision process against another and use to enhance education and guideline compliance/adherence detection and improvement. The invention can be applied to practically any field where predictive modeling (classification and regression) is desired because it relies on extremely broad distributional assumptions that are valid in numerous fields.
机译:本发明解决了现代数据分析技术的两个普遍存在且紧迫的问题。许多现代模式识别技术产生的模型具有出色的可预测性,但是(a)它们是“黑匣子”,即用户不透明; (b)它们太大,和/或价格昂贵,无法在功能较弱的计算平台上执行。本发明通过将其转换成功能上等效的紧凑且易于理解的模型来“打开”黑匣子模型。本发明还将预测模型转换成功能上等效的模型,转换成可以在实践中更容易或更有效地实施和部署的形式。好处包括:模型的可理解性和建模的可辩护性。一个特别有趣的应用是理解人的决策,将人的决策过程或计算机决策过程与另一个决策过程的行为进行比较,并用于增强教育和指南依从性/依从性检测和改进。因为本发明依赖于在许多领域中有效的极其广泛的分布假设,所以本发明实际上可以应用于需要预测建模(分类和回归)的任何领域。

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