Advances in Machine Learning and Data Mining for Astronomy (Hardcover)
暫譯: 天文學中的機器學習與資料探勘進展 (精裝版)

Michael J. Way, Jeffrey D. Scargle, Kamal M. Ali, Ashok N. Srivastava

  • 出版商: CRC
  • 出版日期: 2012-03-29
  • 售價: $6,820
  • 貴賓價: 9.5$6,479
  • 語言: 英文
  • 頁數: 744
  • 裝訂: Hardcover
  • ISBN: 143984173X
  • ISBN-13: 9781439841730
  • 相關分類: Machine LearningData-mining
  • 海外代購書籍(需單獨結帳)

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商品描述

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science.

The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications.

With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

商品描述(中文翻譯)

《機器學習與資料探勘在天文學中的進展》記錄了計算機科學家、統計學家和天文學家之間的多次成功合作,展示了最先進的機器學習和資料探勘技術在天文學中的應用。由於大多數科學領域中數據的龐大數量和複雜性,本書所討論的內容超越了科學與計算機科學各個領域之間的傳統界限。

本書的引言部分提供了天文科學中與健康、社會和物理科學同樣重要的問題背景,特別是分類和聚類分析的概率和統計方面。接下來的部分描述了幾個利用多種機器學習和資料探勘技術的天體物理案例研究。在最後一部分,算法開發者和機器學習及資料探勘的實踐者展示了這些工具和技術在天文應用中的使用方式。

本書由領先的天文學家和計算機科學家撰寫,是機器學習、資料探勘和統計學中許多重要發展的實用指南。它探討了這些進展如何解決當前和未來的天文學問題,並考察了它們如何可能導致資料探勘社群內全新算法的創建。