Imagen de Portada

Classification and Data Science in the Digital Age

Mostrar otras versiones (1)

The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications. Numerous research topics are covered, ranging from statistical inference and modeling to clustering and dimension reduction, from functiona...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Brito, Paula (Editor), Dias, José G. (Editor), Lausen, Berthold (Editor), Montanari, Angela (Editor), Nugent, Rebecca (Editor)
Formato: Electrónico eBook
Lenguaje:inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2023.
Edición:1st ed. 2023.
Colección:Studies in Classification, Data Analysis, and Knowledge Organization,
Materias:
Artificial intelligence > Data processing.
Machine learning.
Data mining.
Multivariate analysis.
Statistics > Computer programs.
Data Science.
Statistical Learning.
Machine Learning.
Data Mining and Knowledge Discovery.
Multivariate Analysis.
Statistical Software.
Acceso en línea:Link to Metadata
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications. Numerous research topics are covered, ranging from statistical inference and modeling to clustering and dimension reduction, from functional data analysis to time series analysis, and network analysis. The applications reflect new analyses in a variety of fields, including medicine, marketing, genetics, engineering, and education. The book comprises selected and peer-reviewed papers presented at the 17th Conference of the International Federation of Classification Societies (IFCS 2022), held in Porto, Portugal, July 19-23, 2022. The IFCS federates the classification societies and the IFCS biennial conference brings together researchers and stakeholders in the areas of Data Science, Classification, and Machine Learning. It provides a forum for presenting high-quality theoretical and applied works, and promoting and fostering interdisciplinary research and international cooperation. The intended audience is researchers and practitioners who seek the latest developments and applications in the field of data science and classification.
Descripción Física:XIV, 416 p. 93 illus., 68 illus. in color. online resource.
ISBN:9783031090349
ISSN:2198-3321
DOI:10.1007/978-3-031-09034-9
Acceso:Open Access

Ejemplares similares