Supervised and Unsupervised Statistical Data Analysis

The contributions in this book offer new insights into the theoretical and practical challenges of supervised and unsupervised learning, highlighting the remarkable breadth of contemporary statistical research while maintaining methodological rigor. Innovative approaches to statistical modeling, add...

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Bibliographic Details

Corporate Author:	SpringerLink (Online service)
Other Authors:	D'Ambrosio, Antonio (Editor), de Rooij, Mark (Editor), De Roover, Kim (Editor), Iorio, Carmela (Editor), La Rocca, Michele (Editor)
Format:	Electronic eBook
Language:	English
Published:	Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edition:	1st ed. 2025.
Series:	Studies in Classification, Data Analysis, and Knowledge Organization,
Subjects:	Machine learning. Statistics . Data mining. Quantitative research. Mathematical statistics > Data processing. Statistical Learning. Statistical Theory and Methods. Data Mining and Knowledge Discovery. Data Analysis and Big Data. Statistics and Computing. Applied Statistics.
Online Access:	https://doi.org/10.1007/978-3-032-03042-9
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