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Data Analysis and Optimization
Название: Data Analysis and Optimization: In Honor of Boris Mirkin's 80th Birthday
Автор: Boris Goldengorin, Sergei Kuznetsov
Издательство: Springer
Год: 2023
Страниц: 447
Язык: английский
Формат: pdf (true)
Размер: 14.7 MB

This book presents the state-of-the-art in the emerging field of Data Science and includes models for layered security with applications in the protection of sites―such as large gathering places―through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. The manipulability of aggregation procedures for the case of large numbers of voters is analyzed from a theoretical point of view and justified by computational experiments involving at least an order of magnitude larger number of voters. Many tree-type structures are considered: from phylogenetic trees representing the main patterns of vertical descent through consensus trees and super- trees widely used in evolutionary studies to combine phylogenetic information contained in individual gene trees. The statistical part of this book studies an impact of data mining and modeling on predictability assessment of time series. New notions of mean values based on ideas of multicriteria optimization are compared to their conventional definitions leading to fresh algorithmic approaches. To summarize, the book presents methods for automated analysis of patterns and models for data of different nature with applications ranging from scientific discovery to business intelligence and analytics. The style of the written chapters allows to recommend this book for senior undergraduate and graduate data mining courses providing a broad yet in-depth review integrating novel concepts from Machine Learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification supported by real life case studies.

Students and professionals specializing in computer and management science, data mining for high-dimensional data, complex graphs, and networks will benefit from many cutting-edge ideas and practically motivated case studies.

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