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The size of sample reference points (n) is determined by the error tolerance limit.
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Whereas by raising the error tolerance below suitable values, noise is introduced to the knowledge-base and the results deteriorate.
The method provides automatic solutions with an accuracy that can be effectively set up by choosing an appropriate value of the error tolerance parameter.
The CLAD model provided the best predictions when limiting the error tolerance to 0.05 followed by the OLS model.
In all cases, the mass of a sequence suggested by an identification method should match that of the reference sequence (subject to the error tolerance of the equipment).
To analyze the error tolerance of the gene-disease identification approach, we performed experiments by randomly removing edges from the gene-interaction network.
We assume the error tolerance is 10−6.
The error tolerance is set as 0.01.
Figure 12 illustrates the result of the error tolerance range.
We set the error tolerance for all algorithms as ε=10−4.
(2) We assume the error tolerance is 10−6.
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