Associations were not significantly different when evaluated by tumour stage or grade (results not shown).
The performance of the proposed framework, when evaluated with different evaluation parameters and compared with the state-of-the art methods like SVM, random forest, bagging, etc., is found to be superior than the available methods.
Clearly different libraries rank differently when evaluated according to different criteria.
Previous research suggests, for example, that biomarkers discovered under this traditional framework may: a) be difficult to reproduce using independent datasets, b) lack predictive robustness when evaluated with different computational prediction model and datasets, c) be more difficult to interpret in the context of previous and emerging evidence [9], [10], [11].
When evaluated with respect to different worlds, it is true of different individuals.
When evaluated with standardized differences, the CGI-ADHD-S score was moderately different (EUR mean = 5.2, NE mean = 4.7, standardized difference = 0.625).
Thus, these biomarkers performed with different effectiveness when evaluated by individual pathological processes such as necrosis, apoptosis, and regeneration.
For example, it may be prudent to apply different criteria when evaluating variant sites with known genotypes or that are common variants compared to those predicted to be heterozygous based solely on the short read data.
Hamels now uses a different metric when evaluating a pitcher's success.
Established models can display a loss of fit when evaluated in different critical care populations [ 42].
