High dimensionality is one of important properties of big data,and dimensionality reduction is an effective method to deal with high-dimensional data.The key point of dimensionality reduction algorithm design is preserving the discriminant information and geometric structure contained in original high-dimensional data set,such that the obtained low-dimensional feature representations not only can characterize the distributional shape of original high-dimensional data set,but also are helpful to correspondin...
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