Get Free Shipping on orders over $89
Nature-Inspired Computation in Data Mining and Machine Learning : Studies in Computational Intelligence - Xing-Shi He

Nature-Inspired Computation in Data Mining and Machine Learning

By: Xing-Shi He (Editor), Xin-She Yang (Editor)

Hardcover | 16 September 2019

At a Glance

Hardcover


$249.75

or 4 interest-free payments of $62.44 with

 or 

Ships in 5 to 7 business days

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.

More in Data Mining

Statistics and Data Handling for Biologists : A Student's Guide - Neil Millar
Microsoft Power BI For Dummies : For Dummies (Computer/Tech) - Jack A. Hyman
Microsoft Excel 365 Bible : Bible - Michael Alexander

RRP $90.95

$65.75

28%
OFF
Coding All-in-One For Dummies : 2nd Edition - Chris Minnick

RRP $69.95

$46.99

33%
OFF
Spark : The Definitive Guide : Big Data Processing Made Simple - Bill Chambers
Fundamentals of Data Engineering : Plan and Build Robust Data Systems - Joe Reis
Advanced Basketball Data Science : With Applications in R - Marco Sandri