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The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1472-6963/12/302/prepub wouldulikeike to acknowledge the China Health and Retirement Longitudinal Study CHARLSS) team for providing data and the training of using the dataset.
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The results of this study can be used to optimize the training of GPs using the EAP.
The findings are limited to the training of novices using a phantom model.
In particular, we performed the feature selection and the training of the classifier using cross-validation only by using the training set.
One allows developers to parallelize the training of their networks using multiple GPUs simultaneously.
We also envisaged interviewer bias and we reduced this by the training of the interviewers used in this study.
The definition of the domain of applicability of the training set using the vectorial representation of the training samples by molecular descriptors prevents a direct application to models trained by structured kernel-based machine learning approaches.
In the training of the networks, we used data recorded in 2005 to 2013.
Filtration of the training set using ART1. 4.
The training of the SVM was conducted using the Java implementation of LibSVM 2.83.
The training of the ANNs was performed using customized software at EXINI Diagnostics.
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