Exact(57)
A GPU was used to accelerate training of the DNN, which made it feasible to perform hyperparameter search to optimize prediction performance with cross validation.
The effectiveness of our extended framework is tested on the tool wear experiments in an industrial high speed computer numerical control milling machine, which can achieve an acceptable prediction performance with the average error of predicted bounds less than 15.0% as well as the average accuracy more than 94.3%.
The 5-fold CV experiments are performed on the train dataset and obtain high prediction performance with 93.9% precision and 81.35% recall when the 11 top-ranked features are used.
The results show that, compared to the TM-21 method, the PF approach achieves better prediction performance, with an error of less than 5% in predicting the long-term lumen maintenance life of LED light sources.
Furthermore, both LMR and NLMR equations indicated similar performance capacity in predicting Q. Nevertheless; the use of NLMR equations resulted in prediction performance with higher accuracy in estimating Q compared to LMR equations.
Further, the proposed approach obtains balanced prediction performance with the under-sampling technique.
Detailed evaluations using the Meetup datasets demonstrate that our prediction frameworks achieves high prediction performance with the proposed features.
As compared with the non-modular approach, the modular approach offers comparable prediction performance with significantly lower overall computation time.
Similar(3)
Our results suggest that the prediction performances with the use of GO terms, regardless which predictive modeling method is used and which criteria is used for comparisons, are always better than those without the use of GO terms.
Analyze zero-inflated models with a Bayesian approach to estimate regression parameters and compare prediction performances with the frequentist approach for applications to ANC visits counter measures.
The prediction performances with individual probes were very high.
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