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RF provided a rank for each of the prediction variables based on mean decrease in accuracy of classification.
However, there is not much difference in accuracy of classification on using this constitutive background in IMR90.
To verify this, we filtered any retained exon intron boundary within different distances of the constitutive exon intron boundaries and found a steady improvement in accuracy of classification with filtering distance.
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The relative importance of each cytokine in the accuracy of classification in these models is shown in Fig. 3a,c.
The summary of benchmarks related to machine learning techniques in terms of accuracy of classification is listed in the Table 2.
Both posteromedial parietal and occipital regions were predictive of conversion, but the parietal region was better in terms of accuracy of classification.
The results show improved accuracy of classification in relatively low computational time with the two-stage feature selection.
The effects of parameters used in the model on the accuracy of classification were also investigated.
The support-set of 3 peaks was chosen to improve the accuracy of classification in cross-validation experiments.
Additionally we tested whether reducing the number of protein peaks in a profile affected the accuracy of classification.
In particular, the leave-one-out accuracy of classification is reduced to unsatisfied 63%%.
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