| 书目名称 | From Curve Fitting to Machine Learning |
| 副标题 | An Illustrative Guid |
| 编辑 | Achim Zielesny |
| 视频video | |
| 概述 | An interactive and illustrative guide to scientific data analysis and computational intelligence.Introduction to curve fitting, clustering and machine learning along with topics like mathematical opti |
| 丛书名称 | Intelligent Systems Reference Library |
| 图书封面 |  |
| 描述 | .The analysis of experimental data is at heart of science from its beginnings. .But it was the advent of digital computers that allowed the execution of highly non-linear and increasingly complex data analysis procedures - methods that were completely unfeasible before. Non-linear curve fitting, clustering and machine learning belong to these modern techniques which are a further step towards computational intelligence..The goal of this book is to provide an interactive and illustrative guide to these topics. It concentrates on the road from two dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with .exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that |
| 出版日期 | Book 20111st edition |
| 关键词 | Dissipation; Energy; Hamilton’s Variational Principle and its Generalization; Variational-Asymptotic Me |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-21280-2 |
| isbn_ebook | 978-3-642-21280-2Series ISSN 1868-4394 Series E-ISSN 1868-4408 |
| issn_series | 1868-4394 |
| copyright | Springer Berlin Heidelberg 2011 |
发表于 2025-3-21 20:07:37
