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The multiple prediction orders method can also be utilized to deal with other multi-target learning problems, such as subcellular location prediction [ 37] and functions of proteins [ 20].
To deal with this complicated statistical systems like that, we adopted the strategy of the multiple prediction orders, ranging from the most likely side effect prediction order to the least one, that is, giving the information to users, which side effect is most likely, which one is the second likely one, and so forth.
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Accordingly, it has become common to use multiple prediction tools, concentrating on the intersecting results, in order to overcome the well-known problems related to MIR targets identification [ 29].
Tsang et al. [32] proposed an intra-prediction algorithm using a single prediction direction instead of multiple prediction directions.
We have previously shown that using multiple prediction methods improves the accuracy of disorder predictions.
Usually the creation of silver standard corpora required a corpus harmonization in order to merge multiple predictions, in the simplest case by applying a voting scheme [13] together with various mention boundary reconciliation strategies (e.g. exact, nested, continuous similarity measure for mention alignments [13]).
We recommend a low window size in the range of 5 to 10 kb in order to visualize multiple predictions in an individual manner.
The success of the intelligence effort so far may explain why Israel has defied multiple predictions that it would carry out military raids on Iranian nuclear facilities.
where L is the linear prediction order and wm,i is the prediction coefficient.
Consequently, multiple predictions for each compound should be combined as follows: For numeric predictions, the mean predicted value is preferable.
Underline sign indicates multiple predictions.
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