Classification and Data Science in the Digital Age
Contributor(s)
Brito, Paula (editor)
Dias, José G. (editor)
Lausen, Berthold (editor)
Montanari, Angela (editor)
Nugent, Rebecca (editor)
Language
EnglishAbstract
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.
Keywords
Classification; Data Science; Clustering; Statistical Learning; Machine Learning; Data Analysis; Mutlivariate Analysis; Statistical Inference; Dimension Reduction; Functional Data Analysis; Time Series Analysis; Network AnalysisDOI
10.1007/978-3-031-09034-9ISBN
9783031090349, 9783031090332, 9783031090349Publisher
Springer NaturePublisher website
https://www.springernature.com/gp/products/booksPublication date and place
Cham, 2023Imprint
Springer International PublishingSeries
Studies in Classification, Data Analysis, and Knowledge Organization,Classification
Algorithms & data structures
Artificial intelligence
Mathematical & statistical software
Machine learning
Data mining
Probability & statistics