“非负矩阵分解”的概念、定义、翻译、参考文献-科学参考

非负矩阵分解

Encyclopedia

理学线性特征提取释
non-negative matrix factorization; NMF非负矩阵分解
非负矩阵分解(non-negative matrix factorization, NMF)是一种常用的矩阵分解算法，基于输入的矩阵，非负矩阵分解算法可将其分解为两个矩阵和都是非负的，即：该方法最早由D.D.Lee和H.S.Seung在1999年于科学杂志《Nature》上提出，它使分解后的所有分量均为非负值，并且达到维数约减。非负矩阵分解现在是计算机视觉、数字信号处理、生物信息工程和机器学习等研究领域中应用最多的高维数据处理方法之一。

单词	非负矩阵分解
释义	非负矩阵分解 Encyclopedia 理学线性特征提取释 non-negative matrix factorization; NMF非负矩阵分解非负矩阵分解(non-negative matrix factorization, NMF)是一种常用的矩阵分解算法，基于输入的矩阵，非负矩阵分解算法可将其分解为两个矩阵和都是非负的，即：该方法最早由D.D.Lee和H.S.Seung在1999年于科学杂志《Nature》上提出，它使分解后的所有分量均为非负值，并且达到维数约减。非负矩阵分解现在是计算机视觉、数字信号处理、生物信息工程和机器学习等研究领域中应用最多的高维数据处理方法之一。
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