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PDF that is composed of PLF and PEF has led to improvement of classifier performance.
The significant improvement of classifier performance by using evolutionary information has further been demonstrated in the ROC analysis.
However, adding M m and M d to the input vector did not result in further improvement of classifier performance (data not shown).
Other values of m were also tested, but did not result in significant improvement of classifier performance for DNA-binding site prediction.
Similarly to the previous example the "hard" learning strategy (γ = 0.1) initially leads to rapid improvement of classifier performance, reaching the maximum performance of 87.7% in 14 iterations.
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Comparison of classifier performance is carried out as well.
AUC gives a measure of classifier performance.
The Area Under Curve (AUC) is used as a reliable index of classifier performance.
Furthermore, the EDSS-dependent improvement of the classifier performance to reach a sensitivity of 78.0%, suggests that the expression of genes involved correlate with patients' neurological findings.
Using this method, Schuller et al. [51] reported an improvement in classifier performance in the domain of speech emotion recognition.
Our results indicate no improvement in classifier performance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com