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Causal Models and Intelligent Data Management

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Cover of 'Causal Models and Intelligent Data Management'

Table of Contents

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    Book Overview
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    Chapter 1 Statistics, Causality, and Graphs
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    Chapter 2 Causal Conjecture
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    Chapter 3 Who Needs Counterfactuals?
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    Chapter 4 Causality: Independence and Determinism
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    Chapter 5 Intelligent Data Analysis and Deep Understanding
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    Chapter 6 Learning Algorithms in High Dimensional Spaces
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    Chapter 7 Learning Linear Causal Models by MML Sampling
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    Chapter 8 Game Theory Approach to Multicommodity Flow Network Vulnerability Analysis
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    Chapter 9 On the Accuracy of Stochastic Complexity Approximations
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    Chapter 10 AI Modelling for Data Quality Control
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    Chapter 11 New Directions in Text Categorization
Attention for Chapter 3: Who Needs Counterfactuals?
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Chapter title
Who Needs Counterfactuals?
Chapter number 3
Book title
Causal Models and Intelligent Data Management
Published by
Springer, Berlin, Heidelberg, January 1999
DOI 10.1007/978-3-642-58648-4_3
Book ISBNs
978-3-64-263682-0, 978-3-64-258648-4
Authors

A. P. Dawid

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