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Please predict whether this patent is acceptable.PATENT ABSTRACT: Systems and methods for executing an unsupervised feature selection algorithm on a processor which directly embeds feature selection into a clustering algorithm using sparse learning are disclosed. The direct embedding of the feature selection, via sparse learning, reduces storage requirement of collected data. In one method, unsupervised feature selection may be accomplished through a removal of redundant, irrelevant, and/or noisy features of incoming high-dimensional data.