rTensor: An R Package for Multidimensional Array (Tensor) Unfolding, Multiplication, and Decomposition

被引:21
作者
Li, James [1 ]
Bien, Jacob [2 ]
Wells, Martin T. [2 ]
机构
[1] Facebook, Cambridge, MA 02142 USA
[2] Cornell Univ, Ithaca, NY 14853 USA
来源
JOURNAL OF STATISTICAL SOFTWARE | 2018年 / 87卷 / 10期
关键词
tensor; multidimensional arrays; S4; Tucker decomposition; multilinear principal components analysis; generalized low rank approximation of matrices; population valued decomposition; CANDECOMP/PARAFAC; tensor singular value decomposition; FACE REPRESENTATION; 2-DIMENSIONAL PCA; FACTORIZATIONS; FRAMEWORK;
D O I
10.18637/jss.v087.i10
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
rTensor is an R package designed to provide a common set of operations and decompositions for multidimensional arrays (tensors). We provide an S4 class that wraps around the base 'array' class and overloads familiar operations to users of 'array', and we provide additional functionality for tensor operations that are becoming more relevant in recent literature. We also provide a general unfolding operation, for which the k-mode unfolding and the matrix vectorization are special cases of. Finally, package rTensor implements common tensor decompositions such as canonical polyadic decomposition, Tucker decomposition, multilinear principal component analysis, t-singular value decomposition, as well as related matrix-based algorithms such as generalized low rank approximation of matrices and popular value decomposition.
引用
收藏
页码:1 / 31
页数:31
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