非负矩阵分解(NMF)初始化的最优方法

Hao Xie, Juan Qiu, Chuanlin Zhang
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引用次数: 0

摘要

提出了一种NMF算法初始化的优化方法。该优化方法可以方便地与现有的NMF算法初始化方法集成。该策略是基于NMF的几何解释,在凸包中,两点连接点之间的交点与概率单纯形的对应边界,用来更新矩阵中初始基向量对应点,使基向量矩阵得到扩展,并且它能更好地包含原始矩阵。许多数值算例表明,与原始初始化相比,该方法可以获得更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Optimal Method for the Initialization of Non-negative Matrix Factorization (NMF) ⋆
An optimization method of the NMF algorithm initialization is proposed. This optimization method can be easily integrated with the existing initialization methods of NMF algorithm. The strategy is based on the geometric interpretation of NMF, in the convex hull, the intersection point between the connect of two points and the corresponding boundary of probability simplex, is used to update the initial basis vectors corresponding point in the matrix, so that the base vector matrix extended, and it can better contain the original matrix. Many numerical examples show that, compared with the original initialization, this method can obtain better results.
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