k_unfold-methods

k_unfold

k_unfold,Tensor-method

tnsr

<p>the index of the mode to unfold on</p>

<p>Unfolding of a tensor by mapping the kth mode (specified through parameter <code>m</code>), and all other modes onto the column space. This the most common type of unfolding operation for Tucker decompositions and its variants. Also known as k-mode matricization.</p>

A set of tools for creation, manipulation, and modeling
of tensors with arbitrary number of modes. A tensor in the context of data
analysis is a multidimensional array. rTensor does this by providing a S4
class 'Tensor' that wraps around the base 'array' class. rTensor
provides common tensor operations as methods, including matrix unfolding,
summing/averaging across modes, calculating the Frobenius norm, and taking
the inner product between two tensors. Familiar array operations are
overloaded, such as index subsetting via '[' and element-wise operations.
rTensor also implements various tensor decomposition, including CP, GLRAM,
MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements
transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some
auxiliary functions include the Khatri-Rao product, Kronecker product, and
the Hamadard product for a list of matrices.

k_unfold-methods: Tensor k-mode Unfolding

Description

Usage

Arguments

Value

Details

References

See Also

Examples