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It is clearly confirmed in these figures that all the optimal training sequences (conventional or proposed) provide the best performance for both the LMMSE and LS estimators.
As a result, the online ECOC techniques proposed provide a feasible and robust way for handling new classes using any base classifier.
The results obtained using different ensembles of hybrid EPUNNs and ERBFNNs show that the functional model and the hybrid algorithms proposed provide a very accurate identification compared to other statistical methodologies used to solve this regression problem.
The two methods proposed provide such non-parametric transformation (i.e. change to ranks), because Spearman is a rank correlation coefficient and RMA includes a quantile normalization.
The reciprocal design and a series of analytical and testing strategies proposed provide a standard procedure for genomic mapping of QTLs involved in the genetic control of complex seed development traits in flowering plants.
While the physiological role of this process remains uncertain, the models proposed provide hypotheses for further work.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com