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Titlebook: Recent Trends and Future Challenges in Learning from Data; Cristina Davino,Francesco Palumbo,Hans A. Kestler Conference proceedings 2024 T

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书目名称Recent Trends and Future Challenges in Learning from Data
编辑Cristina Davino,Francesco Palumbo,Hans A. Kestler
视频video
概述Showcases recent trends and future challenges in learning from data.Presents statistical methods and applications in biology, the social sciences and finance.Emphasizes the role of statistics in disco
丛书名称Studies in Classification, Data Analysis, and Knowledge Organization
图书封面Titlebook: Recent Trends and Future Challenges in Learning from Data;  Cristina Davino,Francesco Palumbo,Hans A. Kestler Conference proceedings 2024 T
描述.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..
出版日期Conference proceedings 2024
关键词Data Analysis; Classification; Clustering; Statistical Models; Supervised Learning; Unsupervised Learning
版次1
doihttps://doi.org/10.1007/978-3-031-54468-2
isbn_softcover978-3-031-54467-5
isbn_ebook978-3-031-54468-2Series ISSN 1431-8814 Series E-ISSN 2198-3321
issn_series 1431-8814
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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