Results 291 to 300 of about 1,759,415 (331)
Modelling the spatial and temporal dynamics in the distribution patterns of African White backed vultures Gyps africanus in the Hwange National Park. [PDF]
Zhuwawo T, Zvidzai M, Mapfumo RB.
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Enhanced machine learning and hybrid ensemble approaches for Coronary Heart Disease prediction. [PDF]
Wanyonyi M +3 more
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Air quality index AQI classification based on hybrid particle swarm and grey wolf optimization with ensemble machine learning model. [PDF]
Elabd E +4 more
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MS-YieldStackNet: multi-source data fusion for wheat yield estimation using a stacked ensemble neural network. [PDF]
Ali W +5 more
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Rester ensemble, savoir ensemble
2023Quels sont les processus sociaux et cognitifs activés entre les enfants dans la vie quotidienne d'un service éducatif pour la petite enfance ? Que signifie faire de l'éducation avec de jeunes enfants ? Comment soutenir la socialité et le partage des connaissances entre les jeunes enfants ? Comment promouvoir un contexte social inclusif dans lequel tous
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Gaussian Ensemble as an Interpolating Ensemble
Physical Review Letters, 1988We consider a noncanonical ensemble which involves a sample thermally connected to a finite heat bath with specific properties. Treating the size of the heat bath as a parameter, we show that static properties of finite samples are ensemble dependent.
, Challa, , Hetherington
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Ensemble manifold regularization
2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up.
Bo, Geng +4 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
We consider tracking as a binary classification problem, where an ensemble of weak classifiers is trained online to distinguish between the object and the background. The ensemble of weak classifiers is combined into a strong classifier using AdaBoost.
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We consider tracking as a binary classification problem, where an ensemble of weak classifiers is trained online to distinguish between the object and the background. The ensemble of weak classifiers is combined into a strong classifier using AdaBoost.
openaire +2 more sources

