Sentence examples for better performance for prediction from inspiring English sources
In addition, results show that the model outperforms other literature models and correlations and exhibits better performance for prediction of experimental data.
The proposed method VIP-RPLSR has the advantages of wider applicability and better performance for NIR prediction of soil N and OC in comparison with PLSR, RPLSR, VIP-PLSR and UVE-PLSR modeling techniques.
LASSO leads to a sparse solution of coefficients corresponding to the most important predictors, and has been known to show better performance for the prediction model selection and better identification of predictors than classical regression methods [ 18].
The STOP-BANG Questionnaire had better performance for the prediction of OSA on home sleep study, and different cut-points for the STOP-BANG score could be selected depending on the preference to exclude SDB (score <3) or predict SDB (score ≥6).
They demonstrated that the inclusion of more genomes (68 vs. 30) resulted in better performance for PPI predictions, however, they did not provide a strategy for bacteria selection.
> -wrap-foot> ourrapproach achieved achieved better performance for direct interaction prediction than for indirect interaction prediction (Table 1).
We expect that our method would achieve better performance for indirect interaction prediction if different mechanisms of indirect DTIs in the MATADOR-based data could be further identified.
We are able to get better performance for these non-canonical site predictions as well.
The results show that, compared with the single measure, the proposed method has better performance for the short-term traffic flow prediction in terms of the accuracy and timeliness.
Results reveal that SVM prediction model achieves better performance for some drugs (Erlotinib, Paclitaxel and PF-2341066 etc).
Compared with the previous results, the constructed tree shows a better performance for the model set samples, but worse prediction rates (Table 2); therefore, the model has again a fairly high sensitivity (100%), but quite low selectivity (57.1%).
