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The results are shown in Table 2. Clearly, the t-test based methods are superior to both Affymetrix Fold Change and absolute difference using transformed data.
From overall evaluation criteria, the DNN based methods are superior to traditional GMM-HMM based method on F1 and micro average with maximal 14%and11%1% error reduction in PD and 7% and 10% in PI, meanwhile keep similar performances on macro average.
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Several studies have suggested that treatment efficiency with the assistance of paper- based methods is superior to computerized systems [ 4- 6].
Experiments on the human genome show that our multi-feature based method is superior in performance to existing exon detection algorithms.
While at lower SNR values, the correlation-based methods are superior to the ML estimator, at higher values of SNR the latter performs better.
For daily data it is clear that the copula-based methods are superior to the others in terms of point estimation and have the added benefit of providing an estimate of the precision of the interpolation, not provided by the others.
Our comparative studies confirmed that tree-based methods are superior to approaches that rely on sequence similarity for inferring phylogenetic relationships.
Most authors believe that it matters very much [ 3] and that guidelines produced using evidence-based methods are superior to other methodologies of development [ 2, 4, 9].
Although the first study was performed only for the PLIER-preprocessed data, this tendency was universally observed for the other preprocessed data: FC-based methods are superior to t-statistic-based methods if the POG is evaluated.
The recent benchmark experience with the leading target-enrichment technologies [ 8, 10] concluded that both PCR- and circularization-based methods are superior to hybrid capture methods with respect to achieved specific and uniform sequence coverage, albeit they are not able to target large regions in a single experiment, which is in contrast an advantage of hybrid capture approaches.
Several comparison studies with three popular wavelet packet decomposition based methods were conducted to show the superior capability of sparsogram in bearing fault diagnosis.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com