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Naive bayes and adaptive boosting have been used as classifiers to analyze the performance.
These algorithms, such as bagging and boosting, have been revealed more significant advantages than signal classifier [1 3, 33 37].
Algorithmically, neural networks [19], relevance vector machines [20], and additive logistic regression with boosting have been applied [21].
Ensemble methods, including RF, bagging, and boosting, have been increasingly applied in bioinformatics.
Ensemble classification methods such as boosting have been applied to the classification of gene expression data and have produced more accurate results [ 8] than the individual models that work alone.
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At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.
Asymmetric boosting has been proposed by several researchers [12, 17, 21 24].
Gate level (WL) voltage boosting has been investigated in[13, 29] to reduce the write-1 latency of STT-RAM.
It should be noted that, to the best of the authors' knowledge, this is the first work that has applied boosting to gait recognition although boosting has been well studied for face recognition [27 29].
It is also not clear if the magnitude of the boosting effect is generalisable to all PPD formulations, although boosting has been documented for most commercial TST formulations.
This finding is important since the existence of endogenous boosting has been proposed to have an effect in reducing the negative effects of varicella vaccination on HZ incidence.
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