Due to the weak homology among ERF proteins outside the AP2/ERF domain, identical classification patterns were obtained with the two clustering methods.
Although the proportions of samples that they reported with identical classification were slightly higher to ours, the rank of concordances was similar with 83% between the 70- and 76-gene signatures, 85% between the 76-gene signature and the GGI, and 92% (the highest agreement) between the 70-gene signature and the GGI.
However, the same study did not evaluate whether identical classification could be obtained by using genes not included in the genomic imbalances as a basis for re-clustering.
For example, with a codebook size of 256, the proposed algorithms achieve similar performance as traditional algorithms with a codebook size of 1024, indicating that the proposed algorithms reduce the computational cost by 75% while achieving almost identical classification accuracy to traditional algorithms.
However, the results did not materially change when restricted to studies with an identical classification of generations as described in the methods nor when contraceptives with desogestrel or gestodene were compared with levonorgestrel (that is, norgestimate was not taken into account when classifying contraceptives into generations) (data not shown).
Similarly, we analyzed the immature 30S particles isolated under high salt condition using the identical image classification method.
In particular, HMSC16 and HMSC21 had identical classification success for all blind‐test fish except those in the fall run (Table 5).
Restricted to studies with an identical classification of generations (see methods section for classification used), the results of each generation compared with non-use remained the same (first generation relative risk 3.2, 95% confidence interval 1.6 to 6.4; second generation 2.6, 1.5 to 4.7; third generation 3.5, 2.0 to 6.1).
We found that iRDA does not perform well on the Lung dataset when compared to CMIM, although both filters display an almost identical classification performance on this particular dataset.
In the design of these systems, diversity is considered as one of the main aspects to be taken into account, since there is no gain in combining identical classification methods.
