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

Language: English

Published by Eliva Press, 2026

9999345883 / 9789999345880

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Seller Inventory # 9789999345880

Title
Efficient Clustering Algorithms for Multivariate Data : A Computational Approach: Integrating Factor Analysis, K-Means, and Validation Measures
Author
Mehmet Cevri
Publisher
Eliva Press
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
9999345883
ISBN 13
9789999345880
Item weight
108 grams
Dimensions
229x152x4 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item7 to 10 business days5 to 7 business days
First itemUS$ 39.80US$ 51.17
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