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The RBF NN model is retrained at the end of each cycle with the most recent data added to the NN training set.
In this scenario, the model is retrained for each new observation.
Then, the model is retrained using the original seed examples and the self-labeled examples.
Then, another set of ligands are docked, the model is retrained and the process is repeated until a certain model efficiency level is reached.
The detection model is retrained over the updated and extended training set which now also includes the acquired examples that are regarded as being very informative.
The first half of the optimization is based on GGD-ILRMA with β=2 and p=1, and the second half is the proposed method with arbitrary parameters, where the NMF source model is retrained using the temporary estimated signal after the first-half optimization.
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The acoustic model was retrained by using clean and dereverberated multi-condition data ('clean+multi-rt').
The regularization parameters alpha and beta were tuned using cross validation and the model was retrained on the entire training set with optimal parameters.
The logistic regression model was retrained with all signature genes as above.
Similarly, to predict the five prognostic subtypes related to cellular phenotypes defined by Sadanandam et al with the outcome signature, the parameters of a proportional odds model were retrained with the six gene proxies from our signature as predictors using cross-validation and classified the patient samples from the two datasets described above.
When a new sample is available, all the models are retrained, and a new model may be included if the ensemble's performance is not satisfactory.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com