Chemometrics for Pattern Recognition (Hardcover)

Richard G. Brereton

Chemometrics for Pattern Recognition (Hardcover)
  • 出版商: Wiley
  • 出版日期: 2009-09-28
  • 售價: $1,590
  • 貴賓價: 9.8 折 $1,558
  • 語言: 英文
  • 頁數: 522
  • 裝訂: Hardcover
  • ISBN: 0470987251
  • ISBN-13: 9780470987254
  • 相關分類: 化學 Chemistry、大數據 Big-data、Data Science

    • 立即出貨 (庫存=1)

相關主題

商品描述

Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of data, and, in parallel, the significant growth in applications especially in biomedical analytical chemical measurements of extracts from humans and animals, together with the increased capabilities of desktop computing. The interpretation of such multivariate datasets has required the application and development of new chemometric techniques such as pattern recognition, the focus of this work.

 

Included within the text are:

  • ‘Real world’ pattern recognition case studies from a wide variety of sources including biology, medicine, materials, pharmaceuticals, food, forensics and environmental science;
  • Discussions of methods, many of which are also common in biology, biological analytical chemistry and machine learning;
  • Common tools such as Partial Least Squares and Principal Components Analysis, as well as those that are  rarely used in chemometrics such as Self Organising Maps and Support Vector Machines;
  • Representation in full colour;
  • Validation of models and hypothesis testing, and the underlying motivation of the methods, including how to avoid some common pitfalls.

 

Relevant to active chemometricians and analytical scientists in industry, academia and government establishments as well as those involved in applying statistics and computational pattern recognition.

商品描述(中文翻譯)

在過去的十年中，模式識別一直是化學計量學中增長最快的領域之一。這得益於自動化儀器（如LCMS、GCMS和NMR等）能夠獲取大量數據的能力的提高，以及在生物醫學分析化學測量（包括人體和動物提取物）以及桌面計算能力的顯著增長。解釋這種多變量數據集需要應用和發展新的化學計量技術，如模式識別，這是本書的重點。

本書包含以下內容：
- 來自生物學、醫學、材料、藥物、食品、法醫學和環境科學等各種來源的“現實世界”模式識別案例研究；
- 方法討論，其中許多方法在生物學、生物分析化學和機器學習中也很常見；
- 常用工具，如偏最小二乘法和主成分分析，以及在化學計量學中很少使用的自組織映射和支持向量機；
- 全彩色圖示；
- 模型驗證和假設檢驗，以及方法的基本動機，包括如何避免一些常見的陷阱。

本書對於從事化學計量學和分析科學的從業人員（包括工業、學術界和政府機構）以及應用統計和計算模式識別的人士都具有相關性。

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