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The paper is related to the error analysis of Support Vector Machine (SVM) classifiers based on reproducing kernel Hilbert spaces. We choose the polynomial kernels as the Mercer kernel and give the error estimate with De La Vallée Poussin means which improve the approximation error. On the other hand, the distortion is replaced by the uniformly boundedness of the Cesàro means. We also introduce...
The maintenance period, the time frame begging from the registration to the expiration of a patent, is an important property used to evaluate the patent's quality. To predict the maintenance period of a patent, a consistent classifier is desirable. The output of a classifier is usually determined by the value of a discriminant function and a decision is made based on this output which does not necessarily...
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