Results 1 to 10 of about 332,101 (116)
clusterBMA: Bayesian model averaging for clustering [PDF]
PLoS ONE, 2023 Various methods have been developed to combine inference across multiple sets of results for unsupervised clustering, within the ensemble clustering literature.
Owen Forbes +9 more
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Bayesian Network Model Averaging Classifiers by Subbagging [PDF]
Entropy, 2022 When applied to classification problems, Bayesian networks are often used to infer a class variable when given feature variables. Earlier reports have described that the classification accuracy of Bayesian network structures achieved by maximizing the ...
Shouta Sugahara, Itsuki Aomi, Maomi Ueno
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Nonlinear predictive model selection and model averaging using information criteria
Systems Science & Control Engineering, 2018 This paper is concerned with the model selection and model averaging problems in system identification and data-driven modelling for nonlinear systems. Given a set of data, the objective of model selection is to evaluate a series of candidate models and ...
Yuanlin Gu +2 more
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Combining Predictions of Auto Insurance Claims
Econometrics, 2022 This paper aims to better predict highly skewed auto insurance claims by combining candidate predictions. We analyze a version of the Kangaroo Auto Insurance company data and study the effects of combining different methods using five measures of ...
Chenglong Ye +5 more
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Frontiers in Energy Research, 2021 In view of the intrinsic complexity of the oil market, crude oil prices are influenced by numerous factors that make forecasting very difficult.
Bai Huang +6 more
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Sensors, 2023 Previous studies investigating multi-sensor fusion for the collection of soil information have shown variable improvements, and the underlying prediction mechanisms are not sufficiently understood for spectrally-active and -inactive properties.
Isabel Greenberg +5 more
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Confidence Distributions for FIC Scores
Econometrics, 2020 When using the Focused Information Criterion (FIC) for assessing and ranking candidate models with respect to how well they do for a given estimation task, it is customary to produce a so-called FIC plot. This plot has the different point estimates along
Céline Cunen, Nils Lid Hjort
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Sensitivity of Survival Analysis Metrics
Mathematics, 2023 Survival analysis models allow for predicting the probability of an event over time. The specificity of the survival analysis data includes the distribution of events over time and the proportion of classes.
Iulii Vasilev +2 more
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Autocorrelation and Parameter Estimation in a Bayesian Change Point Model
Mathematics, 2023 A piecewise function can sometimes provide the best fit to a time series. The breaks in this function are called change points, which represent the point at which the statistical properties of the model change.
Rui Qiang, Eric Ruggieri
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Comparison of Seven Non-Linear Mixed Effect Model-Based Approaches to Test for Treatment Effect
Pharmaceutics, 2023 Analyses of longitudinal data with non-linear mixed-effects models (NLMEM) are typically associated with high power, but sometimes at the cost of inflated type I error.
Estelle Chasseloup, Mats O. Karlsson
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