Kernel knowledge

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Kernel knowledge

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Prior knowledge, in the form of linear inequalities that need to be satisfied over multiple polyhedral sets, is incorporated into a function approximation generated by a linear combination of linear or nonlinear kernels. In addition, the approximation needs to satisfy conventional conditions such as having given exact or inexact function values at certain points. Determining such an approximati...

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Knowledge-Based Nonlinear Kernel Classifiers

Prior knowledge in the form of multiple polyhedral sets, each belonging to one of two categories, is introduced into a reformulation of a nonlinear kernel support vector machine (SVM) classifier. The resulting formulation leads to a linear program that can be solved efficiently. This extends, in a rather unobvious fashion, previous work [3] that incorporated similar prior knowledge into a linea...

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ژورنال

عنوان ژورنال: Current Biology

سال: 2002

ISSN: 0960-9822

DOI: 10.1016/s0960-9822(02)00849-7