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基于改进的Askey-Wilson多项式核函数
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Abstract:
基于Askey-Wilson多项式的性质，给出了两种Askey-Wilson多项式形式，分别与Rbf核函数和三角核函数进行组合，构造混合支持向量机AW核函数。所构造的AW核函数都含有一个重要核参数q，可通过改变q值来调整核函数。实验选取双螺线及6个UCI数据集，比较AW核函数在数据集上的泛化性能和鲁棒性。
Based on the properties of Askey-Wilson polynomials, two forms of Askey-Wilson polynomials are given, which are combined with Rbf kernel function and triangular kernel function respectively to construct a hybrid support vector machine AW kernel function. The constructed AW kernel func-tions all contain an important kernel parameter q, which can be adjusted by changing the q value. The experiment selects the double helix and 6 UCI datasets to compare the generalization perfor-mance and robustness of the AW kernel function on the datasets.
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