Local Linear Embedding with Adaptive Neighbors

Jiaqi Xue, Bin Zhang, Qianyao Qiang

Abstract: Highlights•Linear approximation of LLE. Our model takes the linear mapping into consideration, making it more suitable to handle both linear and non-linear data. Also, outliers can be well dealt with during the linear projection procedure.•Global and local structure. Instead of only consider the local geometry properties, we also consider the global data point relationship to preserve the intrinsic structure. And our model shows robustness to noise and uneven distribution data.•Adaptive neighbor selection. In our model, weight between data and neighbors are updated in order to adjust each data into its optimal neighborhood. Using adaptive neighbor strategy, manifold structure can be kept and then structure learning and feature extraction could be accomplished simultaneously.