Suggestions(1)
Exact(11)
This facilitates cautious classification and motivates a novel data cleaning method.
Combined with cautious classification and data cleaning, we can achieve predictive accuracies of up to 99.6%.
The proposed method was composed of cautious classification and data cleaning, where cautious classification was used to increase the accuracy by restricting predictions to high-confidence instances, whereas data cleaning was used to mitigate the influence of mislabeled training instances.
We showed that there are significant gains from using cautious classification, where prediction is confined to a high confidence instance.
When we apply cautious classification to our classifier, we can achieve near-perfect classification accuracy at the highest P-value cutoffs (Figs. 3 and 4).
Further, cautious classification gave similar curves to those for the non-coding data (Figs. 3 and 4), see Supplementary Figures S6 and S7.
Similar(49)
Therefore, we consider the threshold of 50 as the upper bound in the classification of cautious drivers and the lower bound in the classification of reckless drivers.
However, Hong, Margines and Dey [56], templates must be stored, such as acceleration, deceleration, and curves, which are used for comparison with the driver's maneuvers and a subsequent classification as cautious or reckless.
But one should be cautious about this as, we found that this family classification does largely depend on the microsatellite related origin of these miRNAs.
While the slightly different time-courses of classification accuracy are suggestive, we would like to be cautious in interpreting these, as the experiment was not designed to separate preparation and execution related activity.
Very cautious.
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