data science classification artificial (12 résultats)

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Taschenbuch. Etat : Neu. Data Science, Classification, and Artificial Intelligence for Modeling Decision Making | Javier Trejos (u. a.) | Taschenbuch | Studies in Classification, Data Analysis, and Knowledge Organization | xii | Englisch | 2025 | Springer | EAN 9783031858697 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San José, Costa Rica, July 15 19, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making.Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines.The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification.

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San José, Costa Rica, July 15 19, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making.Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines.The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification. 204 pp. Englisch.

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Paperback. Etat : new. Paperback. This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San Jose, Costa Rica, July 1519, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making.Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines.The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 204 pp. Englisch.