| 书目名称 | Numeric Computation and Statistical Data Analysis on the Java Platform | | 编辑 | Sergei V. Chekanov | | 视频video | | | 概述 | Equips readers with a description.of the Java computational environment for data mining and knowledge discovery.which can be used with several scripting languages, such as Python, Groovy and.Provides | | 丛书名称 | Advanced Information and Knowledge Processing | | 图书封面 |  | | 描述 | Numericalcomputation, knowledge discovery and statistical data analysis integrated withpowerful 2D and 3D graphics for visualization are the key topics of this book. ThePython code examples powered by the Java platform can easily be transformed toother programming languages, such as Java, Groovy, Ruby and BeanShell. Thisbook equips the reader with acomputational platform which, unlike other statistical programs, is not limitedby a single programming language..The authorfocuses 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-linearregression analysis and many other data-mining topics. He discusses how to findregularities in real-world data, how to classify data, and how to process datafor knowledge discoveries. The code snippets are so short that they easily fit intosingle pages..Numeric Computation and Statistical DataAnalysis on the Java Platform. is a great choice for those who want to learn how statisticaldata analysis can be done using popular programming languages, who want tointegrate data analysis algorithms i | | 出版日期 | Textbook 2016 | | 关键词 | Data Analysis; Java Programming Language; Jython/Python; Numeric Computations; Statistics; Data Mining | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-28531-3 | | isbn_softcover | 978-3-319-80371-5 | | isbn_ebook | 978-3-319-28531-3Series ISSN 1610-3947 Series E-ISSN 2197-8441 | | issn_series | 1610-3947 | | copyright | Springer International Publishing Switzerland 2016 |
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发表于 2025-3-21 19:48:58
