基于调和平均测地线核的局部线性嵌入算法

为解决现有局部线性嵌入算法不适合处理非均匀分布数据和未利用距离远点信息的问题,首先引入测地线距离,以便能利用远点信息;然后使用调和平均规范化构造调和平均测地线核矩阵,使算法能更好地处理分布不均匀数据并具有鲁棒性。在UCI数据集上的实验结果表明,改进后的算法能够取得比局部线性嵌入算法更好的降维效果。

A local linear emedding agorithm based on harmonicmean geodesic kernel

An improved algorithm was proposed to overcome the shortcomings of the existing local linear embedding algorithm that was not suitable for the non uniform distribution data and not use the information of distant points. First, to improv the accuracy of the algorithm the geodesic-distance was introduced into the new algorithm in order to take advantage of the information of distant points, and then the harmonic-mean geodesic-kernel matrix was constructed by using the harmonic-mean standardization,which could process robustly non-uniform distribution data. The results of the experiments on UCI data sets showed that the improved algorithm could obtain better performance than the classical local linear embedding algorithm on dimension reduction.