000 03894nam a22005055i 4500
001 978-3-319-28531-3
003 DE-He213
005 20200421112047.0
007 cr nn 008mamaa
008 160323s2016 gw | s |||| 0|eng d
020 _a9783319285313
_9978-3-319-28531-3
024 7 _a10.1007/978-3-319-28531-3
_2doi
050 4 _aQA76.7-76.73
050 4 _aQA76.76.C65
072 7 _aUMX
_2bicssc
072 7 _aUMC
_2bicssc
072 7 _aCOM051010
_2bisacsh
072 7 _aCOM010000
_2bisacsh
082 0 4 _a005.13
_223
100 1 _aChekanov, Sergei V.
_eauthor.
245 1 0 _aNumeric Computation and Statistical Data Analysis on the Java Platform
_h[electronic resource] /
_cby Sergei V. Chekanov.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXXVI, 620 p. 92 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvanced Information and Knowledge Processing,
_x1610-3947
505 0 _aJava Computational Platform -- Introduction to Jython -- Mathematical Functions -- Data Arrays -- Linear Algebra and Equations -- Symbolic Computations -- Histograms -- Scientific Visualization -- File Input and Output -- Probability and Statistics -- Linear Regression and Curve Fitting -- Data Analysis and Data Mining -- Neural Networks -- Finding Regularities and Data Classification -- Miscellaneous Topics -- Using Other Languages on the Java Platform -- Octave-style Scripting Using Java -- Index -- Index of Code Examples.
520 _aNumerical 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.
650 0 _aComputer science.
650 0 _aProgramming languages (Electronic computers).
650 0 _aData mining.
650 1 4 _aComputer Science.
650 2 4 _aProgramming Languages, Compilers, Interpreters.
650 2 4 _aData Mining and Knowledge Discovery.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319285290
830 0 _aAdvanced Information and Knowledge Processing,
_x1610-3947
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-28531-3
912 _aZDB-2-SCS
942 _cEBK
999 _c56971
_d56971