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Reconstructing directional causal networks with random forest: Causality meeting machine learning
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2019Inspired by the decision tree algorithm in machine learning, a novel causal network reconstruction framework is proposed with the name Importance Causal Analysis (ICA). The ICA framework is designed in a network level and fills the gap between traditional mutual causality detection methods and the reconstruction of causal networks. The potential of the
Siyang Leng, Ziwei Xu, Huanfei Ma
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This seminar provides an in-depth exploration of causal machine learning, equipping participants with sophisticated techniques to differentiate causation from correlation using modern machine learning tools integrated with robust econometric methods.
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Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning
Foundations and Trends® in Machine LearningSummary: Decision-making systems based on AI and machine learning have been used throughout a wide range of real-world scenarios, including healthcare, law enforcement, education, and finance. It is no longer far-fetched to envision a future where autonomous systems will drive entire business decisions and, more broadly, support large-scale decision ...
Plečko, Drago, Bareinboim, Elias
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Causal Machine Learning in Marketing
International Journal of Business & Management StudiesThis study reviews three primary purposes of causal machine learning (CML) in marketing, merging impact evaluation of marketing interventions with machine learning algorithms for learning statistical patterns from data. Firstly, CML enables more credible impact evaluation by considering important control variables that simultaneously influence the ...
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Essays in Causal Machine Learning
2021Die vorliegende Thesis umfasst drei Essays aus dem Bereich der kausalen Ökonometrie. Jedes der einzelnen Kapitel ist der Frage gewidmet wie maschinelles Lernen für Standardprobleme der Kausalanalyse verwendet werden kann. Ein erstes, einführendes Kapitel veranschaulicht die Zusammenhänge zwischen den drei folgenden Hauptkapiteln.
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Causal Inspired Trustworthy Machine Learning
Proceedings of the ACM Turing Award Celebration Conference - China 2023, 2023openaire +1 more source
Causal Inference and Causal Machine Learning with Practical Applications
Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD), 2023Somedip Karmakar +2 more
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