Nature Inspired Computation in Data Mining and Machine Learning is popular PDF and ePub book, written by Xin-She Yang in 2019-09-03, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Nature Inspired Computation in Data Mining and Machine Learning can be Read Online from any device for your convenience.

Nature Inspired Computation in Data Mining and Machine Learning Book PDF Summary

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.

Detail Book of Nature Inspired Computation in Data Mining and Machine Learning PDF

Nature Inspired Computation in Data Mining and Machine Learning
  • Author : Xin-She Yang
  • Release : 03 September 2019
  • Publisher : Springer Nature
  • ISBN : 9783030285531
  • Genre : Technology & Engineering
  • Total Page : 273 pages
  • Language : English
  • PDF File Size : 20,5 Mb

If you're still pondering over how to secure a PDF or EPUB version of the book Nature Inspired Computation in Data Mining and Machine Learning by Xin-She Yang, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.

Get Book

Nature Inspired Algorithms and Applications

Nature Inspired Algorithms and Applications Author : S. Balamurugan,Anupriya Jain,Sachin Sharma,Dinesh Goyal,Sonia Duggal,Seema Sharma
Publisher : John Wiley & Sons
File Size : 29,5 Mb
Get Book
Mit diesem Buch soll aufgezeigt werden, wie von der Natur inspirierte Berechnungen eine praktische A...

Computational Intelligence in Data Mining

Computational Intelligence in Data Mining Author : Janmenjoy Nayak,H.S. Behera,Bighnaraj Naik,S. Vimal,Danilo Pelusi
Publisher : Springer Nature
File Size : 19,7 Mb
Get Book
This book addresses different methods and techniques of integration for enhancing the overall goal o...

Swarm Intelligence and Bio Inspired Computation

Swarm Intelligence and Bio Inspired Computation Author : Xin-She Yang,Zhihua Cui,Renbin Xiao,Amir Hossein Gandomi,Mehmet Karamanoglu
Publisher : Newnes
File Size : 16,6 Mb
Get Book
Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decad...

Computational Intelligence in Data Mining

Computational Intelligence in Data Mining Author : Himansu Sekhar Behera,Janmenjoy Nayak,Bighnaraj Naik,Ajith Abraham
Publisher : Springer
File Size : 35,7 Mb
Get Book
The International Conference on “Computational Intelligence in Data Mining” (ICCIDM), after thre...

Evolutionary Machine Learning Techniques

Evolutionary Machine Learning Techniques Author : Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah
Publisher : Springer Nature
File Size : 46,5 Mb
Get Book
This book provides an in-depth analysis of the current evolutionary machine learning techniques. Dis...