Exact(9)
Moreover, this pattern is reproducible despite the fact that test data were generated using entirely different microarray platforms and species from those used in the generation of training data.
Therefore, 23 test data were generated by the pairwise approach; (RR_1): Values were generated randomly and no strategy for combining the values was adopted.
Thus, 23 test data were generated by the pairwise approach; (RR_1): Values were generated randomly and no strategy for combining the values was adopted.
Thus, selecting a total of four values per input, 16 test data were generated by the pairwise approach; (RP_2): The difference from the (RP_1) is that, for each input range, five values were selected instead of two.
Thus, 11 test data were generated by the pairwise approach; (RP_2): The difference from the (RP_1) is that, for each input range, three values were selected instead of two.
Therefore, 13 test data were generated by the pairwise approach; (RP_2): The difference from the (RP_1) is that, for each input range, three values were selected instead of two.
Similar(51)
MMR Test: in the test process, the meta-level test data are generated and the meta-classifiers (h 1,⋯,h N C ) are tested.
A large amount of comprehensive test data was generated.
From an economical point of view, hardware and test labs are expensive and require lead time before test data are generated.
When the test data are generated, these new ranges are used.
The test data are generated by auxiliary devices and transferred over additional networks in HINT.
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