Results 21 to 30 of about 718,596 (262)
British Journal of Sports Medicine, 2004 This article reviews the history, technique, effects, side effects, and detection of blood boosting. It also considers whether or not this particular performance enhancement technique is a thing of the past or a continuing form of abuse among athletes.
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Boosting Techniques for Nonlinear Time Series Models [PDF]
, 2010 Many of the popular nonlinear time series models require a priori the choice of parametric functions which are assumed to be appropriate in specific applications.
Hothorn, Torsten +2 more
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Interpreting uninterpretable predictors: kernel methods, Shtarkov solutions, and random forests
Statistical Theory and Related Fields, 2022 Many of the best predictors for complex problems are typically regarded as hard to interpret physically. These include kernel methods, Shtarkov solutions, and random forests.
T. M. Le, Bertrand Clarke
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Domain Transfer Multiple Kernel Boosting for Classification of EEG Motor Imagery Signals
IEEE Access, 2019 The application of wireless sensors in the brain-computer interface (BCI) system provides great convenience for the acquisition of electroencephalography (EEG) signals.
Mengxi Dai +4 more
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Machine Learning-Based Forecasting of Bitcoin Price Movements
Proceedings of the International Conference on Applied Innovations in ITIn the volatile realm of cryptocurrency markets, this research explores the intricate dance of Bitcoin price dynamics through the lens of machine learning. Employing a multifaceted approach, we harness the power of Long Short-Term Memory (LSTM) networks,
Darko Angelovski +4 more
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PLoS ONE, 2013 Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on
Schmid, Matthias +5 more
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Judgment and Decision Making, 2023 Short-sighted decisions can have devastating consequences, and teaching people to make their decisions in a more far-sighted way is challenging. Previous research found that reflecting on one’s behavior can boost learning from success and failure.
Frederic Becker +4 more
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Popular Ensemble Methods: An Empirical Study
, 2011 An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any of
Maclin, R., Opitz, D.
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Foundations and Innovations in Data Fusion and Ensemble Learning for Effective Consensus
MathematicsEnsemble learning and data fusion techniques play a crucial role in modern machine learning, enhancing predictive performance, robustness, and generalization.
Ke-Lin Du +4 more
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Binary and Ordinal Random Effects Models Including Variable Selection [PDF]
, 2010 A likelihood-based boosting approach for fitting binary and ordinal mixed models is presented. In contrast to common procedures it can be used in high-dimensional settings where a large number of potentially influential explanatory variables is available.
Groll, Andreas, Tutz, Gerhard
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