unfold-methods: Tensor Unfolding

In tensorregress: Supervised Tensor Decomposition with Side Information

Tensor Unfolding

Description

Unfolds the tensor into a matrix, with the modes in rs onto the rows and modes in cs onto the columns. Note that c(rs,cs) must have the same elements (order doesn't matter) as x@modes. Within the rows and columns, the order of the unfolding is determined by the order of the modes. This convention is consistent with Kolda and Bader (2009).

Usage

unfold(tnsr, row_idx, col_idx)

Arguments

tnsr	the Tensor instance
row_idx	the indices of the modes to map onto the row space
col_idx	the indices of the modes to map onto the column space

Details

unfold(tnsr,row_idx=NULL,col_idx=NULL)

Value

matrix with prod(row_idx) rows and prod(col_idx) columns

References

T. Kolda, B. Bader, "Tensor decomposition and applications". SIAM Applied Mathematics and Applications 2009, Vol. 51, No. 3 (September 2009), pp. 455-500. URL: https://www.jstor.org/stable/25662308.

Examples

tnsr <- rand_tensor()
matT3<-unfold(tnsr,row_idx=2,col_idx=c(3,1))

tensorregress documentation built on July 9, 2023, 7:23 p.m.