A Multiscale Approach for Nonnegative Matrix Factorization with Applications to Image Classification
نویسنده
چکیده
We use a multiscale approach to reduce the time to produce the nonnegative matrix factorization (NMF) of a matrix A, that is, A ≈ WH. We also investigate QR factorization as a method for initializing W during the iterative process for producing the nonnegative matrix factorization of A. Finally, we use our approach to produce nonnegative matrix factorizations for classifying images and compare it to the standard approach in terms of classification accuracy.
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