Dimensionality Reduction Using a Randomized Projection Algorithm: Preliminary Results
نویسندگان
چکیده
We describe an implementation and experiments with a low-distortion randomized projection algorithm [LINI94] that can reduce the number of dimensions in the data by a considerable amount. The performance of the randomized algorithm is compared with that of a popular technique---Principal Component Analysis (PCA). The experiments show that the randomized projection algorithm consistently outperforms the PCA.
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تاریخ انتشار 2001