Statistical Learning and Modeling in Data Analysis: Methods and Applications (2021) (Paperback)
 
作者: Simona Balzano 
書城編號: 19184752


售價: $1800.00

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出版社: Springer Verlag Gmbh
出版日期: 2021/04/24
重量: 0.28 kg
ISBN: 9783030699437
 
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商品簡介
Chapter 1 - Interpreting Effects in Generalized Linear Modeling (Alan Agresti, Claudia Tarantola, and Roberta Varriale)
Chapter 2 - ACE, AVAS and Robust Data Transformations: Performance of Investment Funds (Anthony C. Atkinson, Marco Riani, Aldo Corbellini, and Gianluca Morelli) Chapter 3 - Predictive Principal Component Analysis (Simona Balzano, Maja Bozic, Laura Marcis, and Renato Salvatore)
Chapter 4 - Robust model-based learning to discover new wheat varieties and discriminate adulterated kernels in X-ray images (Andrea Cappozzo, Francesca Greselin, and Thomas Brendan Murphy)
Chapter 5 - A dynamic model for ordinal time series: an application to consumers' perceptions of inflation (Marcella Corduas) Chapter 6 - Deep learning to jointly analyze images and clinical data for disease detection (Federica Crobu and Agostino Di Ciaccio)
Chapter 7 -Studying Affiliation Networks through Cluster CA and Blockmodeling (Daniela D'Ambrosio, Marco Serino, and Giancarlo Ragozini)
Chapter 8 - Sectioning Procedure on Geostatistical Indices Series of Pavement Road Profiles (Mauro D'Apuzzo, Rose-Line Spacagna, Azzurra Evangelisti, Daniela Santilli, and Vittorio Nicolosi)
Chapter 9 - Directional supervised learning through depth functions: an application to ECG waves analysis (Houyem Demni) Chapter 10 - Penalized vs. contrained approaches for clusterwise linear regression modelling (Roberto Di Mari, Stefano Antonio Gattone, and Roberto Rocci)
Chapter 11 - Effect measures for group comparisons in a two-component mixture model: a cyber risk analysis (Maria Iannario and Claudia Tarantola)
Chapter 12 - A Cram
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