When the sample size is small, as is often the case in microarray studies, KNN is also suitable to use as Ripley [ 32] indicates that most other non-parametric classification methods, such as kernel density estimation based methods, aim to model the class-conditional densities and thus need a very large training set to be successful.
The analytic models based method aims to use mathematical equations to address both multi-physic and economic characteristics of a product.
In this direction, we present a SVM based method aimed at facilitating the identification of fungal adhesins.
BN structure can be learned by score-based methods, aiming to identify the structure(s) that "best" describe the data.
Due to the lack of publicly available clinical corpora, most existing TM systems operating on clinical texts (e.g., [ 23, 25]) employ dictionary-based methods, aiming to map mentions of clinical concepts within the texts to entries in the UMLS Metathesaurus [ 26].
These model-based methods aim to capture the sequencing process described above in a statistical model from which base-call probabilities are usually obtained.
Though a future consultation, based on Delphi methods, aiming to move towards consensus or, at least, give a clearer depiction of the disparity in opinion, should not be ruled out, it would need to be very focused and limited in its scope to ensure a good response.
Therefore, patients with low self-efficacy and self-empowerment may benefit from life coaching as it is based on methods aimed to improve these characteristics [ 28, 29].
Other approaches to generating haplotypes on a genome-wide scale include cloning- and dilution- based methods that aim to reduce the complexity of phasing by separating the genomic DNA into pools that contain DNA that is either maternally or paternally derived, with some of the most comprehensive molecular haplotypes on a genome-wide scale produced through the use of fosmid clones [ 21- 24].
Ordinary Differential Equation based methods [18] [30], aim to learn a set of ODEs describing the time evolution of target genes as a function of their likely regulators.
Traditional defect prediction methods aim to build the prediction model based on historical data.
