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These facts may explain the improved performance when classifying RET variants as compared to generalized prediction tools available on-line.
Gene-specific prediction algorithms have been shown to be an improvement over existing generalized prediction tools, where a larger data set 'n' for training algorithms may not compensate for lower quality of phenotype information.
A form suitable for non-linear models is the Generalized Prediction Error criterion [ 27]: where γ is the effective number of parameters in the network, E is the error sum of squares, N is the number of data points in the training set and σ is the variance of the noise of the data.
The proposed method can form a basis of a generalized prediction method for flow-generated noise produced by multiple elements.
A number of investigators have tried to develop a generalized prediction method for flow-generated noise produced by in-duct elements in a ventilation system.
Note that the distributions found are approximations used to provide a generalized prediction of the propensity of distinctiveness.
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Comparison of the proposed model predictions with the results from two empirical models currently being implemented in design works, a neural network-based model from literature and also the field data shows that the EPR model is capable of capturing, predicting and generalizing predictions to unseen data cases, for lateral load bearing capacity of piles with very high accuracy.
However, it is challenging to generalize predictions of sediment yield because it is influenced by many factors.
Importantly, our model has the ability to generalize predictions to the previously unseen cases.
After maximizing the prediction power the utility of generalizing predictions on different array experiments and platforms were assessed.
Alternative methods, beyond traditional machine learning approaches that assume training and test sets from the same dataset/domain, would be necessary to generalize predictions and enhance biological conclusions.
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