Description: 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
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