Chemometrics for Pattern Recognition (Hardcover)
暫譯: 化學計量學與模式識別

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)

在過去十年中，模式識別已成為化學計量學中增長最快的領域之一。這一增長受到自動化儀器（如 LCMS、GCMS 和 NMR 等）的能力提升的催化，這些儀器能夠獲取大量數據；同時，生物醫學分析化學測量人類和動物提取物的應用顯著增長，加上桌面計算能力的提升。對這些多變量數據集的解釋需要應用和開發新的化學計量技術，如模式識別，這也是本書的重點。

文本中包含：
- 來自生物學、醫學、材料、製藥、食品、法醫學和環境科學等多種來源的「現實世界」模式識別案例研究；
- 討論方法，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（Partial Least Squares）和主成分分析（Principal Components Analysis），以及在化學計量學中較少使用的工具，如自組織映射（Self Organising Maps）和支持向量機（Support Vector Machines）；
- 全彩色的表現；
- 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。

本書對於活躍的化學計量學家和行業、學術界及政府機構的分析科學家，以及那些從事統計和計算模式識別應用的人士具有相關性。

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