Statistical Learning and Modeling in Data Analysis Statistical Learning and Modeling in Data Analysis
Studies in Classification, Data Analysis, and Knowledge Organization

Statistical Learning and Modeling in Data Analysis

Methods and Applications

Simona Balzano والمزيد
    • ‏149٫99 US$
    • ‏149٫99 US$

وصف الناشر

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk.
The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11–13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG’s goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.

النوع
علم وطبيعة
تاريخ النشر
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١٣ يوليو
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
Springer International Publishing
البائع
Springer Nature B.V.
الحجم
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‫م.ب.‬
Innovations in Classification, Data Science, and Information Systems Innovations in Classification, Data Science, and Information Systems
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Handbook of Latent Variable and Related Models Handbook of Latent Variable and Related Models
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Advances in Distribution Theory, Order Statistics, and Inference Advances in Distribution Theory, Order Statistics, and Inference
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The Skew-Normal and Related Families The Skew-Normal and Related Families
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Data Science Data Science
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Challenges at the Interface of Data Analysis, Computer Science, and Optimization Challenges at the Interface of Data Analysis, Computer Science, and Optimization
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Statistical Models and Learning Methods for Complex Data Statistical Models and Learning Methods for Complex Data
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Supervised and Unsupervised Statistical Data Analysis Supervised and Unsupervised Statistical Data Analysis
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Recent Trends and Future Challenges in Learning from Data Recent Trends and Future Challenges in Learning from Data
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Statistical Models and Methods for Data Science Statistical Models and Methods for Data Science
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