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In brief, for the first training data that contains only histone acetylation information, good classification accuracy was achieved for around one third of all TFs tested (e.g. Table S1a); however, for the second dataset that includes both histone methylation and histone acetlylation features, almost half of all TFs tested were well classified by histone modifications (e.g. Table 1).
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Entropy, a measure of classification accuracy, was good at 90%. Specific prescription medications were found to strongly influence group membership.
These demonstrated that the data length of 300 ms can achieve good classification results of SEMG signals and the classification accuracy was not significantly improved after the data length exceeded 300 ms.
Because the sample size was not balanced between the 'good' and 'poor' groups, the classification accuracy was defined as the average of classification accuracy of the group with good prognosis and that of the group with poor prognosis.
Classification accuracy was 89%.
The reported classification accuracy was over 80%.
AUC results from the ROC curve were 'excellent' for girls and boys 10 14 years of age (0.97 and 0.98, respectively); for girls and boys aged 5 9 years classification accuracy was 'good' (0.88) for girls and 'poor' (0.66) for boys.
The classification accuracy was 100percentt.
In this study, the overall classification accuracy was 86.6%.
Statistical significance of classification accuracy was determined by permutation testing.
In this study, the averaged classification accuracy was 74%.
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