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It is therefore essential to develop general approaches and robust methods that are able to overcome the limitation of the small number of training instances and reduce the influence of uncertainties so as to produce reliable classification results.
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As evidenced in Idris and Muhammed [20] for e-mail spam identification, the mAIS is proficient at detecting "non-self" instances and significantly reducing FPs and FNs.
For future work, we plan to optimize the generation of action templates by eliminating redundant information (i.e., clustering similar instances or forgetting unused instances), and therefore reducing classification times.
In a second step the authors (MZ, GB) analyzed the generated category system, identified instances of overlapping and reduced the number of categories to 15.
For instance, reduced protein translation may attenuate ER stress in critical tissues and reduce progression and severity of age-related diseases due to accumulation of misfolded proteins.
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