It compares the accuracy rate of classification in different kernel function, results show that the kernel-based SVM method which use combined feature vectors can give the best performance.
对比不同核函数下的分类准确率，结果表明，组合特征向量的SVM方法对大鱼际掌纹的初步二分类效果较好。
参考来源 - 基于SVM的大鱼际掌纹图像二分类法·2,447,543篇论文数据，部分数据来源于NoteExpress
PRN combined feature selection algorithm is proposed.
并提出改进的PRN组合特征选择算法。
A furthermore experiment proved that the combined feature selection method is effective.
最后通过实验验证组合特征抽取方法的有效性。
The reason of difference is analyzed and a new method named Combined Feature Selection is put forward.
分析了产生差异的原因，并提出一种适合于中文环境的特征选取方法：组合特征选取方法。
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