Numeric Computation and Statistical Data Analysis on the Java Platform / by Sergei V. Chekanov.

Format:

Book

Author/Creator:

Chekanov, S. V. (Sergei V.), author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Advanced information and knowledge processing 1610-3947

Advanced Information and Knowledge Processing, 1610-3947

Language:

English

Subjects (All):

Programming languages (Electronic computers).

Data mining.

Programming Languages, Compilers, Interpreters.

Data Mining and Knowledge Discovery.

Local Subjects:

Programming Languages, Compilers, Interpreters.

Data Mining and Knowledge Discovery.

Physical Description:

1 online resource (XXVI, 620 pages) : 92 illustrations.

Edition:

First edition 2016.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

System Details:

text file PDF

Summary:

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.

Contents:

Java 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.

Other Format:

Printed edition:

ISBN:

978-3-319-28531-3

9783319285313

Access Restriction:

Restricted for use by site license.