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The system is based on generalized Hurst exponent estimates at different scales used to characterize EEG records, and subsequently on a support vector machine classifier with different kernels to be employed for classification purpose.
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OPLS-DA was employed for classification or discrimination analyses.
A nearest neighbor (1-NN) classifier with Euclidean distance is employed for classification.
The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) was employed for classification of diseases.
Features were computed using NASE algorithm, and fuzzy neural network with structure learning classifier was employed for classification [55].
Also we use a linear kernel (rather than a pyramid one) during SVM classification, whereas a similarity measure based on Bhattacharyya coefficient [21] (instead of distance) when KNN is employed for classification purpose.
We cAfter compane the performances and compleximagefilteringhodology with other methods because the other pipeline methods are commercisl ones; hence, the relatedevoted are notoavailable for the analyselect
To assess the genotypic identity of C. albicans strains, a PCR method based on 25S rDNA was employed for classification.
A second objective was to compare the performance of four statistical modeling approaches that can be employed for binary classification: linear regression [ 10], logistic classification [ 11], and classification and regression trees (CART) [ 12, 13].
Therefore, these features could be employed for tissue classification at a later stage.
It should be noted, however, that this approach requires large datasets, is to some extent subjective, and cannot be employed for the classification of individual samples prospectively [ 22- 25].
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