Efficient Clustering Algorithms for Multivariate Data: A Computational Approach: Integrating Factor Analysis, K-Means, and Validation Measures

Cevri, Mehmet

ISBN 10: 9999345883 / ISBN 13: 9789999345880

Published by Eliva Press, 2026

About this Item

Seller Inventory # I-9789999345880

Bibliographic Details

• Title: Efficient Clustering Algorithms for Multivariate Data: A Computational Approach: Integrating Factor Analysis, K-Means, and Validation Measures
• Publisher: Eliva Press
• Publication Date: 2026
• Language: English
• ISBN 10: 9999345883
• ISBN 13: 9789999345880
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Efficient Clustering Algorithms for Multivariate Data: A Computational Approach As the scale and complexity of multivariate datasets grow across scientific disciplines, the need for robust, scalable, and computationally efficient analysis methods has never been more urgent. This book introduces a novel, hybrid algorithmic framework that bridges the gap between dimensionality reduction and cluster validation to uncover the hidden structures within large datasets. At the core of this methodology is a powerful integration of Factor Analysis and K-Means clustering, optimized through the automated utilization of the Silhouette index. By leveraging the advanced algebraic and computational capabilities of Mathematica, the author provides a step-by-step blueprint for executing high-dimensional data partitioning without sacrificing mathematical precision.