Recent Advances in Hybrid Metaheuristics for Data Clustering

by De, Sourav; Dey , Sandip; Bhattacharyya, Siddhartha

• ISBN13: 9781119551591
• ISBN10: 1119551595
• eBook ISBN(s): 9781119551607
• Edition: 1st
• Format: Hardcover
• Copyright: 2020-08-24
• Publisher: Wiley
• More Book Details

Summary

An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques

Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics and their application to data clustering. Metaheuristics are designed to tackle complex clustering problems where classical clustering algorithms have failed to be either effective or efficient. The authors—noted experts on the topic—provide a text that can aid in the design and development of hybrid metaheuristics to be applied to data clustering.

The book includes performance analysis of the hybrid metaheuristics in relationship to their conventional counterparts. In addition to providing a review of data clustering, the authors include in-depth analysis of different optimization algorithms. The text offers a step-by-step guide in the build-up of hybrid metaheuristics and to enhance comprehension. In addition, the book contains a range of real-life case studies and their applications. This important text:

• Includes performance analysis of the hybrid metaheuristics as related to their conventional counterparts
• Offers an in-depth analysis of a range of optimization algorithms
• Highlights a review of data clustering
• Contains a detailed overview of different standard metaheuristics in current use
• Presents a step-by-step guide to the build-up of hybrid metaheuristics
• Offers real-life case studies and applications

Written for researchers, students and academics in computer science, mathematics, and engineering, Recent Advances in Hybrid Metaheuristics for Data Clustering provides a text that explores the current data clustering approaches using a range of computational intelligence techniques.

Author Biography

Sourav De, PhD, is an Associate Professor of Computer Science and Engineering at Cooch Behar Government Engineering College, West Bengal, India.

Sandip Dey, PhD, is an Assistant Professor of Computer Science at Sukanta Mahavidyalaya, Dhupguri, Jalpaiguri, India.

Siddhartha Bhattacharyya, PhD, is a Professor of Computer Science and Engineering at CHRIST (Deemed to be University), Bangalore, India.

Table of Contents

Preface

1. Metaheuristic Algorithms in Fuzzy Clustering

2. Hybrid Harmony Search Algorithm for Feature Selection Problem In the Text Clustering Application

3. Adaptive Position Based Crossover in Genetic Algorithm for Data Clustering

4. Application of Machine learning in the social network

5. Predicting Students’ Grade Using ID3, CART and Multi Class SVM: A Case Study

6. Cluster Analysis of Health Care Data using Hybrid Metaheuristic Algorithm

7. Performance Efficiency Analysis through Metaheuristic Knowledge Engine

8. Magnetic Resonance Image Segmentation Using Quantum Inspired Modified Genetic Algorithm (QIMfGA) Based FCM

9. A Hybrid Approach Using K-Means and Artificial Bee Colony Algorithms for Image Clustering