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Learning machine maps to the Predictor component.
In the predictive auto-scaling problem domain, the Predictor component corresponds to the learning machine of the learning process.
In the auto-scaling domain, the Predictor component corresponds to the learning machine of the leaning process.
Therefore, to improve the accuracy of the Predictor component, the risk minimization principle should be determined based on the complexity of the prediction techniques (i.e., the VC-dimension) and the training dataset size.
Applying the theory of uniform convergence to the auto-scaling problem domain concludes that the convergence rate bounds in the auto-scaling domain are based on the complexity (i.e., VC-dimension) of the regression model that is used in the Predictor component.
The workload pattern complexity is the main driving factor of the Predictor component's VC-dimension.
Similar(54)
Migration is said to be a predictor of component failure [ 51] On the other hand, limited early migration could be a seating effect of cementless cups without having consequences on the outcome.
The loading plot shows that gasoline emissions were the most important predictor (both components), whereas diesel more strongly influenced the second component and secondary NO3 − influenced primarily the first component.
Explanatory variables may enter the model in two ways: either as predictors of the relationship with EQ-5D within each of the individual classes, as in standard regression, or as predictors of component membership.
Important predictors and components of QOL following stroke will vary at different periods following the event.
20 Because several of the potential predictors are components of the response criteria, one might expect that greater baseline values would be associated with greater response.
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