Cause Effect Pairs in Machine Learning
2019 ed.
Book Details
Format
Paperback / softback
ISBN-10
3030218120
ISBN-13
9783030218126
Edition
2019 ed.
Publisher
Springer Nature Switzerland AG
Imprint
Springer Nature Switzerland AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Nov 5th, 2020
Print length
372 Pages
Product Classification:
Machine learningPattern recognitionImage processing
KSh 16,200.00
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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.
This book provides both tutorial material on the state-of-the-art on cause-effect pairs and exposes the reader to more advanced material, with a collection of selected papers. Supplemental material includes videos, slides, and code which can be found on the workshop website.
Discovering causal relationships from observational data will become increasingly important in data science with the increasing amount of available data, as a means of detecting potential triggers in epidemiology, social sciences, economy, biology, medicine, and other sciences.
Get Cause Effect Pairs in Machine Learning by Alexander Statnikov at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer Nature Switzerland AG and it has 372 pages.
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