Journal ArticleDOI
Pattern Recognition and Machine Learning
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TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.Abstract:
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.read more
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Journal ArticleDOI
Bayesian model selection for group studies.
TL;DR: The hierarchical Bayesian approach is considerably more robust than either of the other approaches in the presence of outliers and is expected to prove useful for a wide range of group studies, not only in the context of DCM, but also for other modelling endeavours, e.g. comparing different source reconstruction methods for EEG/MEG.
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Homo Heuristicus: Why Biased Minds Make Better Inferences
Gerd Gigerenzer,Henry Brighton +1 more
TL;DR: The study of heuristics shows that less information, computation, and time can in fact improve accuracy, in contrast to the widely held view that less processing reduces accuracy.
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Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation
TL;DR: This paper analyzes the statistical properties, bias and variance, of the k-fold cross-validation classification error estimator (k-cv) and proposes a novel theoretical decomposition of the variance considering its sources of variance: sensitivity to changes in the training set and sensitivity to changed folds.
Ministry of Education and Science of the Russian Federation
TL;DR: The abstract should follow the structure of the article (relevance, degree of exploration of the problem, the goal, the main results, conclusion) and characterize the theoretical and practical significance of the study results.
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A review on lithium-ion battery ageing mechanisms and estimations for automotive applications
Anthony Barré,Benjamin Deguilhem,Sebastien Grolleau,Mathias Gerard,Frédéric Suard,Delphine Riu +5 more
TL;DR: In this paper, the authors present a summary of techniques, models, and algorithms used for battery ageing estimation, going from a detailed electrochemical approach to statistical methods based on data, and their respective characteristics are discussed.