General Kernel Optimization Model Based on Kernel Fisher Criterion
In this paper a general kernel optimization model based on kernel Fisher criterion (GKOM) is presented. Via a data-dependent kernel function and maximizing the kernel Fisher criterion, the combination coefficients of different kernels can be learned adaptive to the input data. Finally positive empirical results on benchmark datasets are reported.
KeywordsClassification Performance Kernel Optimization Combination Coefficient Wisconsin Breast Cancer Pima Indian Diabetes
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