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Weighted Local Discriminant Preservation Projection Ensemble Algorithm with Embedded Micro-noise
High-dimensional data often cause the "curse of dimensionality" in data processing. Dimensionality reduction can effectively solve the curse of dimensionality and has been widely used in highdimensional data processing. However, the existing dimensionality reduction algorithms neglect the effect of noise injection, failing to account for the datasets of large variance within classes and not effectively considering the stability of dimensionality reduction. To solve the problems, this paperdoi:10.1109/access.2019.2944427 fatcat:ieygyihw25eozl3tfak7eavvkq