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The key advantage of using wavelet transform (WT) based methods is the high signal compression ability of wavelets, making them suitable for modeling of nonstationary environmental parameters with high information content, such as short timescale solar irradiance.
The core of the decision making mechanism of these network, or graph theory based methods, is the connectivity matrix of the network, i.e. which nodes are inter-connected.
For the problem addressed in this study, we believe that policy based methods is the natural choice for three reasons: Policy based methods can learn explicitly an optimal stochastic policy [16], which is our goal.
Although the major limitation of SVM based methods is the requirement of fixed-length input patterns, however it is completely independent of sequence similarity.
One downside of HMM based methods is the need for a training set (generally originating from annotated regions of the genome) which necessarily guides the method towards the recognition of regions which are characteristically similar to the training set.
One advantage of Maximum Likelihood reconstruction of ancestral states (over parsimony based methods) is the ability to incorporate a time component that is estimated by branch lengths on the phylogeny.
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Multivariate statistics based, machine learning based, and pattern matching based methods are the most frequently adopted methodologies summarized in this article.
The previous analyses show that the tetranucleotide based methods are the most adequate methods to use to detect HTs in most cases.
Culture based methods are the gold standard for diagnosing invasive pneumococcal disease (IPD).
For a fair comparison, parameter settings of PSO based methods are the same.
The most common design based method is the 'then' test [ 6].
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