Data Mining Using Neural Networks
A Guide for Statisticians
Taylor & Francis (Publisher)
Published on 1. August 2020
Book
Hardback
300 pages
978-1-4398-7532-2 (ISBN)
Description
A concise, easy-to-understand guide to using neural networks in data mining for mathematics, engineering, psychology, and computer science applications, this book compares how neural network models and statistical models are used to tackle data analysis problems. It focuses on the top of the hierarchy of the computational process and shows how neural networks can perform traditional statistical methods of analysis. The book includes some classical and Bayesian statistical inference results and employs R to illustrate the techniques.
More details
Series
Language
English
Place of publication
Washington
United States
Target group
Professional and scholarly
College/higher education
Students and researchers in statistics, computer science, and related areas.
Illustrations
50 s/w Abbildungen
50 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-4398-7532-2 (9781439875322)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Author
Pennsylvania State University, University Park, USA
Content
Introduction. Fundamental Concepts on Neural Networks. Some Common Neural Networks Models. Multivariate Statistics Neural Networks. Regression Neural Network Models. Survival Analysis and Other Networks.