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On Feature Selection for Genomic Signal Processing and Data Mining
2007
Machine Learning for Signal Processing
An effective data mining system lies in the representation of pattern vectors. The most vital information to be represented is the characteristics embedded in the raw data most essential for the intended applications. In order to extract a useful high-level representation, it is desirable that a representation can provide concise, invariant, and/or intelligible information on input patterns. The curse of dimensionality has traditionally been a serious concern in many genomic applications. For
doi:10.1109/mlsp.2007.4414275
fatcat:at3rnrj7u5eyrkohbnuqr6jrny