CAJ | 학술논문

在基于核方法的分类问题中，核函数及其参数选择皆对分类结果具有重要影响，通常基于经验选择核函数或基于多核优化方法确定核函数的权系数。针对GF空间的多项式核函数，在范数限定条件下利用多核学习方法优化多项式权系数，实现多项式核函数的优化。实验结果表明，算法优化得到的多项式核函数其分类性能优于常用的单核函数，与多核方法相当，并在分类中取得良好的效果。
재기우핵방법적분류문제중，핵함수급기삼수선택개대분류결과구유중요영향，통상기우경험선택핵함수혹기우다핵우화방법학정핵함수적권계수。침대GF공간적다항식핵함수，재범수한정조건하이용다핵학습방법우화다항식권계수，실현다항식핵함수적우화。실험결과표명，산법우화득도적다항식핵함수기분류성능우우상용적단핵함수，여다핵방법상당，병재분류중취득량호적효과。
In classification problem based on the kernel method , kernel function and its parameters have a significant effect on the classification performance .Generally, we select kernel function by experience and weighted coefficient of multiple kernel function which is determined by the multiple kernel optimizing method . Under the norm restricted condition , we utilize multiple kernel learning method to optimize the weighted coefficient of polynomial kernel function based on GF space , and the optimization of polynomial kernel function can be achieved.The experiments results show that the algorithm 's classification performance based on polynomial kernel function in this paper is better than popular used single kernel function , and meet the multiple kernel method 's match;and it perform well in the classification research .