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A new unsupervised feature selection algorithm, based on the concept of shared nearest neighbor distance between pattern pairs, is developed. A multi-objective framework is employed for the preservation of sample similarity, along with dimensionality reduction of the feature space. A reduced set of samples, chosen to preserve sample similarity, serves to reduce the effect of outliers on the feature...
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