Recent Advances in Hybrid Metaheuristics for Data Clustering

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Sourav De, Sandip Dey, Siddhartha Bhattacharyya
John Wiley & Sons, Aug 24, 2020 - Computers - 200 pages

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.

 

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Contents

Metaheuristic Algorithms in Fuzzy Clustering
1
Hybrid Harmony Search Algorithm to Solve the Feature Selection
19
Adaptive PositionBased Crossover in the Genetic Algorithm for Data
39
Application of Machine Learning in the Social Network
61
Predicting Students Grades Using CART ID3 and Multiclass
85
Cluster Analysis of Health Care Data Using Hybrid NatureInspired
101
Performance Analysis Through a Metaheuristic Knowledge
113
Magnetic Resonance Image Segmentation Using a QuantumInspired
129
A Hybrid Approach Using the kmeans and Genetic Algorithms
151
Index
173
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About the author (2020)

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.

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