Navigating Complexity - Statistical Methods, Data Analysis, and Machine Learning for Actionable Insights

Navigating Complexity: Statistical Methods, Data Analysis, and Machine Learning for Actionable Insights

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English | 6 September 2026 | ISBN-10: 3032320089 | 304 pages| Epub PDF (True) | 63 MB
This volume gathers selected, peer-reviewed contributions presented at the 19th Conference of the International Federation of Classification Societies (IFCS 2026), held on 14–16 July 2026 in Milan, Italy. Reflecting the volume’s motto, Navigating Complexity – Statistical Methods, Data Analysis, and Machine Learning for Actionable Insights, the papers showcase modern methodologies and real-world applications designed to extract actionable insights from intricate data. The topics span a wide range of areas within statistics, machine learning, and data science, including model-based clustering, Bayesian methods, anomaly detection, and predictive modeling. Novel and tailored models are proposed for complex data types, such as mixed-type, compositional, and functional data. Furthermore, advanced statistical concepts and cutting-edge artificial intelligence techniques are explored, underscoring the interdisciplinary effort required to address complex challenges in today’s data-driven landscape.
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