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Data Analysis for Complex Systems
A Linear Algebra Approach
Besorgungstitel - wird vorgemerkt | Lieferzeit: Besorgungstitel - Lieferbar innerhalb von 10 Werktagen I
Artikel-Nr:
9780691139180
Veröffentl:
1940
Erscheinungsdatum:
25.12.1940
Seiten:
168
Autor:
Greg Leibon
Sprache:
Englisch
Beschreibung:
Greg Leibon is chief technology officer and cofounder of Coherent Path, a company specializing in predictive analytics. Scott D. Pauls is professor of mathematics at Dartmouth College. Dan Rockmore is the William H. Neukom 1964 Distinguished Professor of Computational Science at Dartmouth.
The analysis of complex systems-from financial markets and voting patterns to ecosystems and food webs-can be daunting for newcomers to the subject, in part because existing methods often require expertise across multiple disciplines. This book shows how a single technique-the partition decoupling method-can serve as a useful first step for modeling and analyzing complex systems data. Accessible to a broad range of backgrounds and widely applicable to complex systems represented as high-dimensional or network data, this powerful methodology draws on core concepts in network modeling and analysis, cluster analysis, and a range of techniques for dimension reduction. The book explains these and other essential concepts and provides several real-world examples to illustrate how a data-driven approach can illuminate complex systems.