Название: Statistical Models and Methods for Data Science
Автор: Leonardo Grilli, Monia Lupparelli, Carla Rampichini
Издательство: Springer
Год: 2023
Страниц: 186
Язык: английский
Формат: pdf (true), epub
Размер: 18.0 MB
This book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with Data Science. Numerous topics are covered, ranging from statistical inference and modelling to clustering and factorial methods, and from directional data analysis to time series analysis and small area estimation. The applications deal with new developments in a variety of fields, including medicine, finance, engineering, marketing, and cyber risk. Analyzing categorical data in Machine Learning generally requires a coding strategy. This problem is common to multivariate statistical techniques, and several approaches have been suggested in the literature. This article proposes a method for analyzing categorical variables with neural networks. Both a supervised and unsupervised approaches were considered, in which the variables can have high cardinality. Some simulated data applications illustrate the interest in the proposal.
Автор: Владимир Посмыгаев
