神经网络和计算-学习算法和应用

T. Chow, Siu-Yeung Cho
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引用次数: 68

摘要

这本书涵盖了神经网络特别强调先进的学习方法和应用。它包括了一些实际的问题,如权值初始化、学习的延迟和局部极小值的逃避,这些都是很多现有的关于这个领域的书没有涉及到的。此外,本书强调了重要的特征选择问题,由于处理大型数据集的困难,这使许多神经网络从业者感到困惑。它还包含一些有趣的信息技术、工程和生物信息学应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Networks and Computing - Learning Algorithms and Applications
This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area. Additionally, the book highlights the important feature selection problem, which baffles many neural networks practitioners because of the difficulties handling large datasets. It also contains several interesting IT, engineering and bioinformatics applications.
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