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At the same time with the decrease of time correlation parameter τ from 0.9 to 0.7, the randomness of the speed between the epoch duration increases resulting in the reduction of prediction inaccuracy.
In training process, the initial structure of the network is trained, and then the architecture of the trained network is optimized for reduction of prediction errors in generalization process.
In addition, models that included a residual polygenic effect resulted in regression coefficients considerably closer to 1 than models without a polygenic effect, which indicates a reduction of prediction bias from including polygenic effects.
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How to compute the prediction order K is a crucial step since it plays an important role for the reduction of the prediction errors.
The proposed tuning method leads to significant reduction of roughness prediction errors in machining operations in comparison to techniques currently used.
Figure 4 shows the relative reduction of the prediction error according to the number of splits.
Sensory attenuation could, thus, be due to bottom-up neural sharpening, facilitation, and/or fatigue, or to top-down reduction of perceptual prediction error.
Sample uniformity, particle size, and consistency in sample thickness on the diamond cell were found to be the most important factors in obtaining consistent spectral acquisition and error reduction for prediction of unknown samples.
When compared to the maximum number of folds that could be predicted for either of these methods (using the 5-species alignment for EvoFold and the 4-species alignment for RNAz), our pipeline for reducing false positives resulted in a 55.5% reduction of EvoFold predictions and an 85.4% reduction in RNAz predictions (Figure S1).
Although the DISOPRED2 SVM offers adjustable specificity, and so allows some reduction of under-prediction as a whole, we were unable to tune it to specifically improve long-region prediction.
DOI: http://dx.doi.org/10.7554/eLife.11945.021 10.7554/eLiFigure45.022 Figure 7 figure supplement 1. Dimensionality reduction of LFP predictions from attractor network model of competition via mutual inhibition.
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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