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To do this, it is "taught" by being fed a series of training inputs and then told what the answer should be in each case.
Several input configurations are tested, including, reduced sets of training inputs (analysis runs), training inputs of high and low fidelity, two sampling processes for these inputs (i.e., random and stratified sampling) and two different IM representations.
However, they generalize poorly at locations far from their training inputs, making those predictions have high variance (low precision).
Here, the first term represents the average reconstruction error over all training inputs.
Figures 6 and 7 show the magnitude and phase LUT entries for different training inputs.
Time series of the translator position along some sinusoidal trajectories were selected as training inputs.
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If training input points and models are simultaneously optimized, the generalization performance would be further improved.
The geometrical properties of the tubular joints were used as the training input data.
The trace collection can be viewed as the training input for this model.
Note that this strategy does not prevent future studies from including visual information as additional training input.
On the other hand, an artificial neural network (ANN) can provide a very flexible mapping based on the training input.
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CEO of Professional Science Editing for Scientists @ prosciediting.com