Название: Model-Based Clustering and Classification for Data Science: With Applications in R Автор: Charles Bouveyron, Gilles Celeux, T. Brendan Murphy
Издательство: Cambridge University Press
Год: 2019
Страниц: 447
Язык: английский
Формат: pdf (true)
Размер: 61.0 MB
Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code
Название: Павел Дмитриев. Сборник произведений (12 книг)