Data mining in EDA - Basic principles, promises, and constraints

Li-C. Wang, M. Abadir
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引用次数: 19

Abstract

This paper discusses the basic principles of applying data mining in Electronic Design Automation. It begins by introducing several important concepts in statistical learning and summarizes different types of learning algorithms. Then, the experience of developing a practical data mining application is described, including promises that are demonstrated through positive results based on industrial settings and constraints explained in their respective application contexts.
EDA中的数据挖掘——基本原则、承诺和约束
本文讨论了数据挖掘在电子设计自动化中应用的基本原理。它首先介绍了统计学习中的几个重要概念,并总结了不同类型的学习算法。然后,描述了开发实际数据挖掘应用程序的经验,包括通过基于各自应用环境中解释的工业设置和约束的积极结果来证明的承诺。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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