NMFStrategyIterative-class

This class provides a specific implementation for the
 generic function <code>run</code> -- concretising the virtual
 interface class <code><links4class>NMFStrategy</links4class></code>, for NMF
 algorithms that conform to the following iterative schema
 (starred numbers indicate mandatory steps): <ul><li>1. Initialisation</li><li>2*. Update the
 model at each iteration</li><li>3. Stop if some criterion
 is satisfied</li><li>4. Wrap up</li></ul> 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 <cite>Lee et al. (2001)</cite>, which are specially
 suitable to be cast into this simple schema.

This package provides a framework to perform Non-negative
        Matrix Factorization (NMF). It implements a set of already
        published algorithms and seeding methods, and provides a
        framework to test and develop new algorithms.

NMFStrategyIterative-class: Interface for Algorithms: Implementation for Iterative NMF Algorithms

Description

Arguments

References