Causation And Counterfactuals
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Causation And Counterfactuals
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Author : John Collins
language : en
Publisher: MIT Press
Release Date : 2004-06-25
Causation And Counterfactuals written by John Collins and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-25 with Philosophy categories.
One philosophical approach to causation sees counterfactual dependence as the key to the explanation of causal facts: for example, events c (the cause) and e (the effect) both occur, but had c not occurred, e would not have occurred either. The counterfactual analysis of causation became a focus of philosophical debate after the 1973 publication of the late David Lewis's groundbreaking paper, "Causation," which argues against the previously accepted "regularity" analysis and in favor of what he called the "promising alternative" of the counterfactual analysis. Thirty years after Lewis's paper, this book brings together some of the most important recent work connecting—or, in some cases, disputing the connection between—counterfactuals and causation, including the complete version of Lewis's Whitehead lectures, "Causation as Influence," a major reworking of his original paper. Also included is a more recent essay by Lewis, "Void and Object," on causation by omission. Several of the essays first appeared in a special issue of the Journal of Philosophy, but most, including the unabridged version of "Causation as Influence," are published for the first time or in updated forms. Other topics considered include the "trumping" of one event over another in determining causation; de facto dependence; challenges to the transitivity of causation; the possibility that entities other than events are the fundamental causal relata; the distinction between dependence and production in accounts of causation; the distinction between causation and causal explanation; the context-dependence of causation; probabilistic analyses of causation; and a singularist theory of causation.
Making Things Happen
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Author : James Woodward
language : en
Publisher: Oxford University Press, USA
Release Date : 2003
Making Things Happen written by James Woodward and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Causation categories.
In doing so, he shows how the manipulationist account both illuminates important features of successful causal explanation in the natural and social sciences and avoids the counterexamples and difficulties that infect alternative approaches, from the deductive-nomological model onward."--BOOK JACKET.
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
The Book Of Why
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Author : Judea Pearl
language : en
Publisher: Penguin UK
Release Date : 2018-05-15
The Book Of Why written by Judea Pearl and has been published by Penguin UK this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-15 with Philosophy categories.
The hugely influential book on how the understanding of causality revolutionized science and the world, by the pioneer of artificial intelligence 'Wonderful ... illuminating and fun to read' Daniel Kahneman, Nobel Prize-winner and author of Thinking, Fast and Slow 'Correlation does not imply causation.' For decades, this mantra was invoked by scientists in order to avoid taking positions as to whether one thing caused another, such as smoking and cancer, or carbon dioxide and global warming. But today, that taboo is dead. The causal revolution, sparked by world-renowned computer scientist Judea Pearl and his colleagues, has cut through a century of confusion and placed cause and effect on a firm scientific basis. Now, Pearl and science journalist Dana Mackenzie explain causal thinking to general readers for the first time, showing how it allows us to explore the world that is and the worlds that could have been. It is the essence of human and artificial intelligence. And just as Pearl's discoveries have enabled machines to think better, The Book of Why explains how we too can think better. 'Pearl's accomplishments over the last 30 years have provided the theoretical basis for progress in artificial intelligence and have redefined the term "thinking machine"' Vint Cerf
Causation And Explanation
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Author : Stathis Psillos
language : en
Publisher: Routledge
Release Date : 2014-12-18
Causation And Explanation written by Stathis Psillos and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-18 with Philosophy categories.
What is the nature of causation? How is causation linked with explanation? And can there be an adequate theory of explanation? These questions and many others are addressed in this unified and rigorous examination of the philosophical problems surrounding causation, laws and explanation. Part 1 of this book explores Hume's views on causation, theories of singular causation, and counterfactual and mechanistic approaches. Part 2 considers the regularity view of laws and laws as relations among universals, as well as recent alternative approaches to laws. Part 3 examines the issues arising from deductive-nomological explanation, statistical explanation, the explanation of laws and the metaphysics of explanation. Accessible to readers of all levels, this book provides an excellent introduction to one of the most enduring problems of philosophy.
Events And Their Names
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Author : Jonathan Bennett
language : en
Publisher: Oxford University Press
Release Date : 1988
Events And Their Names written by Jonathan Bennett and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Philosophy categories.
This is a study of events and their place in our language and thought. The author discusses what kind of item an event is, how the language of events works and how these two themes are interrelated. He argues that most of the supposedly metaphysical literature on events is really about semantics of their names, and that the true metaphysic of events - known by Leibniz and rediscovered by Jaegwon Kim - has not been universally accepted because it has been obscured by a false semantic theory.
Actual Causality
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Author : Joseph Y. Halpern
language : en
Publisher: MIT Press
Release Date : 2016-08-12
Actual Causality written by Joseph Y. Halpern and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-12 with Computers categories.
Explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression.
Causality
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Author : Judea Pearl
language : en
Publisher: Cambridge University Press
Release Date : 2009-09-14
Causality written by Judea Pearl and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-14 with Computers categories.
Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence ...
Understanding Counterfactuals Understanding Causation
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Author : Christoph Hoerl
language : en
Publisher: Oxford University Press, USA
Release Date : 2011-11-03
Understanding Counterfactuals Understanding Causation written by Christoph Hoerl and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-03 with Philosophy categories.
Twelve essays explore what bearing empirical findings might have on philosophical concerns about counterfactuals and causation, and how, in turn, work in philosophy might help clarify issues in empirical work on the relationships between causal and counterfactual thought.
Causal Inference In Statistics
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Author : Judea Pearl
language : en
Publisher: John Wiley & Sons
Release Date : 2016-01-25
Causal Inference In Statistics written by Judea Pearl and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-25 with Mathematics categories.
CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.