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Автор: Isabelle Guyon (Editor), Alexander Statnikov (Editor), Berna Bakir Batu (Editor)
Издательство: Springer
Год: 2019
Формат: true pdf/epub
Страниц: 372
Размер: 18.1 Mb
Язык: English
This book presents ground-breaking advances in the domain of causal structure learning. The problem of distinguishing cause from effect (“Does altitude cause a change in atmospheric pressure, or vice versa?”) is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of the ChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a “causal mechanism”, in the sense that the values of one variable may have been generated from the values of the other.