Relief Algorithm RELIEF is considered one of the most successful algorithms for

assessing the quality of features due to its simplicity and effectiveness.

It has been recently proved that RELIEF is an online algorithm

that solves a convex optimization problem with a marginbased

objective function. Starting from this mathematical interpretation,

we propose a novel feature extraction algorithm, referred

to as LFE, as a natural generalization of RELIEF. LFE collects

discriminant information through local learning, and is solved as

an eigenvalue decomposition problem with a closed-form solution.

A fast implementation is also derived. Experiments on synthetic

and real-world data are presented. The results demonstrate that

LFE performs significantly better than other feature extraction algorithms

in terms of both computational efficiency and accuracy