Numeric Computation and Statistical Data Analysis on the Java Platform

  • Sergei V.┬áChekanov

Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Sergei V. Chekanov
    Pages 1-25
  3. Sergei V. Chekanov
    Pages 27-84
  4. Sergei V. Chekanov
    Pages 85-130
  5. Sergei V. Chekanov
    Pages 131-186
  6. Sergei V. Chekanov
    Pages 187-206
  7. Sergei V. Chekanov
    Pages 207-217
  8. Sergei V. Chekanov
    Pages 219-249
  9. Sergei V. Chekanov
    Pages 251-296
  10. Sergei V. Chekanov
    Pages 297-349
  11. Sergei V. Chekanov
    Pages 351-397
  12. Sergei V. Chekanov
    Pages 399-430
  13. Sergei V. Chekanov
    Pages 431-473
  14. Sergei V. Chekanov
    Pages 475-504
  15. Sergei V. Chekanov
    Pages 505-526
  16. Sergei V. Chekanov
    Pages 527-546
  17. Sergei V. Chekanov
    Pages 547-565
  18. Sergei V. Chekanov
    Pages 567-613
  19. Back Matter
    Pages 615-620

About this book


Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language.

The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages.

Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project and will be appreciated by many data-analysis scientists, engineers and students.


Data Analysis Java Programming Language Jython/Python Numeric Computations Statistics Data Mining

Authors and affiliations

  • Sergei V.┬áChekanov
    • 1
  1. 1.HEP DivisionArgonne National LaboratoryLemontUSA

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-319-28529-0
  • Online ISBN 978-3-319-28531-3
  • Series Print ISSN 1610-3947
  • Series Online ISSN 2197-8441
  • Buy this book on publisher's site
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