Cause Effect Pairs in Machine Learning -
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Présentation Cause Effect Pairs In Machine Learning de Format Broché
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Résumé : Sommaire:
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 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.