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By generating our datasets through an evolution strategy not wedded to any specific model, we achieved datasets that represent the multiplicity of models possible under the desired attribute construction of high-order interaction without low-order interaction.
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The imbalanced datasets achieved from Keel-dataset repository [59, 60] as described in Table 2.
Scaling up to larger geographical areas can be achieved using datasets from other countries to link water body typologies to distribution ranges of migratory fish species.
Best results were achieved by datasets which use a multitude of input data, namely infrared and microwave satellite data, as well as observations from rain gauges (usually GPCC) for bias correction.
This consideration can be seen in the results achieved in Dataset I.
The model species C. reinhardtii is well studied, with 261 Sequence Reads Achieve (SRA) datasets (totally 1150 Gb) available at NCBI.
The results have been analysed based on various sizes of datasets, better results have been achieved with increasing dataset size.
99.98% classification rate is achieved in testing datasets.
Definition of phenotypes and pathways demands very large datasets achieved by combining data from multiple studies.
The recognition accuracy achieved on these datasets demonstrates that the proposed approach has an abundant discriminating power of recognizing the variety of actions.
Significant improvement in accuracy is achieved for some datasets for the two families of induction algorithms used: decision trees and Naive-Bayes.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com