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However the percentage of these HPVs is very low and for absolute HR or LR classification, transformation studies in combination with follow up epidemiological studies are necessary.
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Based on the complexity characteristics of the data set classification, the transformation of the subset of the data set would be completed.
SVM classification including transformation of the input space by means of linear, polynomial, quadratic or rbf kernels, which define non-linear decision surfaces, was adopted for the first two approaches.
This classification and transformations are based on Kiryakova's studies in representing the generalized hypergeometric functions as fractional differintegral operators of three basic elementary functions.
Except this, AGC demonstrates the best performances than the other state-of-the-art techniques due to its better classification and appropriate transformation function.
Encountering a special group of students very eager to explore the world of linear algebra, we initiated a classification of linear transformations of the Euclidean plane R2 via ellipses.
The problem transformation methods transform the multi-label classification problem either into one or more single-label classification or regression problems, and there have been many learning algorithms depending on transformation methods.
Many approaches to transform classification problems from non-linear to linear by feature transformation have been recently presented in the literature.
Moreover, with the discriminative information integrated into the spectral space transformation, the classification performance of S3C is more robust than that of the kernel classifiers.
In this paper, we have three major concerns: (i) appropriate classification along with (ii) transformation of an image for acceptable contrast enhancement with (iii) low computational complexity.
The individual identification is the main part of the proposed system and consists of three steps: feature extraction, feature space transformation, and classification.
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