This class provides a specific implementation for the
generic function run
-- concretising the virtual
interface class NMFStrategy-class
, for NMF
algorithms that conform to the following iterative schema
(starred numbers indicate mandatory steps):
This schema could possibly apply to all NMF algorithms, since these are essentially optimisation algorithms, almost all of which use iterative methods to approximate a solution of the optimisation problem. The main advantage is that it allows to implement updates and stopping criterion separately, and combine them in different ways. In particular, many NMF algorithms are based on multiplicative updates, following the approach from Lee et al. (2001), which are specially suitable to be cast into this simple schema.
signature(object =
"NMFStrategyIterative", y = "matrix", x = "NMFfit")
:
Runs an NMF iterative algorithm on a target matrix
y
.
signature(object =
"NMFStrategyIterative")
: Show method for objects of
class NMFStrategyIterative
Lee DD and Seung H (2001). "Algorithms for non-negative
matrix factorization." _Advances in neural information
processing systems_.