Bayesian semi non-negative matrix factorisation
作者： Albert Vilamala Muñoz , Alfredo Vellido Alcacena , Luis Antonio Belanche Muñoz , None
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摘要: Non-negative Matrix Factorisation (NMF) has become a standard method for source identification when data, sources and mixing coefficients are constrained to be positive-valued. The recently been extended allow negative-valued data in the form of Semi-and Convex-NMF. In this paper, we re-elaborate Semi-NMF within full Bayesian framework. This provides solid foundations parameter estimation and, importantly, principled address problem choosing most adequate number describe observed data. proposed is preliminarily evaluated here real neuro-oncology problem.
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