Many linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices.
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Nov 15, 2016 · Three popular dimension reduction methods, namely principal component analysis (PCA), fourth order blind identification (FOBI) and sliced inverse regression ( ...
Many linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices.
Many linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices.
Many linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices.
Three popular dimension reduction methods, namely principal component analysis (PCA), fourth order blind identification (FOBI) and sliced inverse regression ( ...
This work focuses on one-step M-scatter matrices and proposes a new implementation of ICS based on a pivoted QR factorization of the centered data set that ...
Many linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices.
Apr 24, 2017 · In this letter, we develop asymptotic as well as bootstrap tests for the dimension based on the popular fourth-order blind identification method ...
Many linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices.