Items related to Cause Effect Pairs in Machine Learning (The Springer...
Cause Effect Pairs in Machine Learning (The Springer Series on Challenges in Machine Learning) - Hardcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About this title" may belong to another edition of this title.
Search results for Cause Effect Pairs in Machine Learning (The Springer...
Stock Image
Cause Effect Pairs in Machine Learning.
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Seller rating 4 out of 5 stars
XVI, 372 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. The Springer Series on Challenges in Machine Learning. Sprache: Englisch. Seller Inventory # 9057GB
Quantity: 1 available
Stock Image
Cause Effect Pairs in Machine Learning (The Springer Series on Challenges in Machine Learning)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In. Seller Inventory # ria9783030218096_new
Quantity: Over 20 available
Seller Image
Cause Effect Pairs in Machine Learning
Published by
Springer International Publishing, 2019
ISBN 10: 3030218090
ISBN 13: 9783030218096
New
Hardcover
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive reference for those interested in the cause-effect problem, and how to tackle them using machine learning algorithmsIncludes six tutorial chapters, beginning with the simplest cases and common methods, to alg. Seller Inventory # 332921122
Quantity: Over 20 available
Seller Image
Cause Effect Pairs in Machine Learning
Published by
Springer International Publishing, Springer Nature Switzerland Nov 2019, 2019
ISBN 10: 3030218090
ISBN 13: 9783030218096
New
Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 theChaLearn 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. 388 pp. Englisch. Seller Inventory # 9783030218096
Quantity: 2 available
Seller Image
Cause Effect Pairs in Machine Learning
Published by
Springer International Publishing, Springer Nature Switzerland, 2019
ISBN 10: 3030218090
ISBN 13: 9783030218096
New
Hardcover
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 theChaLearn 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. Seller Inventory # 9783030218096
Quantity: 1 available
Stock Image
Cause Effect Pairs in Machine Learning (The Springer Series on Challenges in Machine Learning)
Seller: California Books, Miami, FL, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # I-9783030218096
Quantity: Over 20 available
Stock Image
Cause Effect Pairs in Machine Learning
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. pp. XVI, 372 122 illus., 90 illus. in color. 1 Edition NO-PA16APR2015-KAP. Seller Inventory # 26384553258
Quantity: 4 available
Stock Image
Cause Effect Pairs in Machine Learning
Print on DemandSeller: Majestic Books, Hounslow, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Print on Demand pp. XVI, 372 122 illus., 90 illus. in color. Seller Inventory # 379350773
Quantity: 4 available
Seller Image
Cause Effect Pairs in Machine Learning
Published by
Springer International Publishing, Springer Nature Switzerland Nov 2019, 2019
ISBN 10: 3030218090
ISBN 13: 9783030218096
New
Hardcover
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 388 pp. Englisch. Seller Inventory # 9783030218096
Quantity: 2 available
Stock Image
Cause Effect Pairs in Machine Learning
Print on DemandSeller: Biblios, Frankfurt am main, HESSE, Germany
Seller rating 4 out of 5 stars
Condition: New. PRINT ON DEMAND pp. XVI, 372 122 illus., 90 illus. in color. Seller Inventory # 18384553248
Quantity: 4 available