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Learning is achieved by stochastic gradient-descent using a mean-squared error training objective.
We show that the Kalman recursion procedure can be simplified by the optimal minimum mean square error training design.
A 3 × 3 experimental design (N = 169), manipulating preobservation performance cues (positive, negative, or none) and the type of intervention (halo error training, structured recall memory, or none), was conducted.
To avoid human error, training systems should be implemented and standard operational procedures should be provided to the operators.
The only authors to do so are Cook et al. (2008), who evaluated the effects of a workshop on error training, performance dimension training, behavioural observation training and frame of reference training using lecture, video and facilitated discussion.
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Nevertheless, neural networks have been criticized for their long trial-and-error training process since the optimal configuration is not known a priori.
"In a business enterprise environment, even simple applications can be very costly when you factor in errors, training and the productivity loss that is often a result," he said.
It highlights the need to reduce human error, increase training and inspections.
The relative error of training and testing sets were 2.11% and 2.6%, respectively.
Figure 6 Relative error from training of previous half-year's data traffic load.
These were mean square error (mse), training time and correlation coefficient (R2).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com