Classification, (Big) Data Analysis and Statistical Learning Classification, (Big) Data Analysis and Statistical Learning
Studies in Classification, Data Analysis, and Knowledge Organization

Classification, (Big) Data Analysis and Statistical Learning

Francesco Mola والمزيد
    • ‏89٫99 US$
    • ‏89٫99 US$

وصف الناشر

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8–10, 2015.

النوع
علم وطبيعة
تاريخ النشر
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٢١ فبراير
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.‬
Advanced Statistical Methods for the Analysis of Large Data-Sets Advanced Statistical Methods for the Analysis of Large Data-Sets
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Studies in Theoretical and Applied Statistics Studies in Theoretical and Applied Statistics
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Topics in Theoretical and Applied Statistics Topics in Theoretical and Applied Statistics
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Advances in Data Analysis Advances in Data Analysis
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Models for Data Analysis Models for Data Analysis
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From Data and Information Analysis to Knowledge Engineering From Data and Information Analysis to Knowledge Engineering
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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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