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Recent Trends and Future Challenges in Learning from Data

This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the mo...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Davino, Cristina (Editor), Palumbo, Francesco (Editor), Wilhelm, Adalbert F. X. (Editor), Kestler, Hans A. (Editor)
Formato: Electrónico eBook
Lenguaje:inglés
Publicado: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edición:1st ed. 2024.
Colección:Studies in Classification, Data Analysis, and Knowledge Organization,
Materias:
Quantitative research.
Data mining.
Mathematical statistics > Data processing.
Statistics .
Machine learning.
Data Analysis and Big Data.
Data Mining and Knowledge Discovery.
Statistics and Computing.
Statistical Theory and Methods.
Applied Statistics.
Statistical Learning.
Acceso en línea:https://doi.org/10.1007/978-3-031-54468-2
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Descripción
Sumario:This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: “Avoiding drowning in the data: recent trends and future challenges in learning from data”. The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance.
Descripción Física:X, 153 p. 40 illus., 35 illus. in color. online resource.
ISBN:9783031544682
ISSN:2198-3321
DOI:10.1007/978-3-031-54468-2

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