A biologist's guide to model selection and causal inference
نویسندگان
چکیده
منابع مشابه
Causal Models Guide Analogical Inference
Computational models of analogical inference have assumed that inferences about the target are generated solely by “copying with substitution and generation” from the source, guided by a mapping based on similarity and parallel structure. In contrast, work in philosophy of science has stressed that analogical inference is based on causal models of the source and target. In two experiments, we s...
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We recently proposed a theoretical integration of analogical transfer with causal learning and inference (Lee & Holyoak, 2008). A Bayesian theory of learning and inference based on causal models (Lee, Holyoak & Lu, 2009) accounts for the fact that judgments of confidence in analogical inferences are partially dissociable from measures of the quality of the mapping between source and target anal...
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Slides accompanying this material are available at http://clopinet.com/isabelle/ Projects/MLSS08/. We focus in the chapter on the problem of model selection. The rest of the topics covered in the class are developed in tutorials on feature selection (Guyon and Elisseeff, 2003; Guyon et al., 2006a) and causality (Guyon et al., 2007a; Guyon, 2008; Guyon et al., 2009a). Nowadays, there are many ma...
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Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology studen...
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ژورنال
عنوان ژورنال: Proceedings of the Royal Society B: Biological Sciences
سال: 2021
ISSN: 0962-8452,1471-2954
DOI: 10.1098/rspb.2020.2815