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Both approaches achieved their aims.
Both approaches achieved comparable results.
While the proposed approaches achieved the lowest E tot score, there were very few false alarms compared to miss errors.
The approaches achieved comparable values for the ITF metric while maintaining a significantly higher amount of pixels.
On the PIM subset the multi-task approaches achieved a significantly lower MSE compared to the tSVM for all targets.
These approaches achieved excellent results on certain iris datasets, but cannot be adapted to arbitrary iris datasets.
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We can see that all the three approaches achieve a throughput of 100% in all cases.
Therefore, these two approaches achieve an SLO violation balance across the ten applications.
Though collaborative filtering approaches achieves great success, there are some shortcomings.
Meanwhile, on average, single feature-based approaches achieve an AUC of 0.61.
Again, all four approaches achieve better performance on the hybrid PPI data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com