Work in progress - Developing a R package for Factorization Machines (FM)
Factorization machines (FM) are a generic approach that allows to mimic most factorization models by feature engineering. This way, factorization machines combine the generality of feature engineering with the superiority of factorizatin models in estimating interactions between categorical variables of large domain. Libfm is a software implementation for factorization machines that features stochastic gradient descent (SGD) and alternating least squares (ALS) optimization as well as Bayesian inference using Markov Chain Monte Carlo (MCMC)[1]. FM has also been implemented in Python: pyFM.
R is a functional programming language especially designed for statistical analysis. It will be handy to have a R-version of FM.
[1] Steffen Rendle (2012): Factorization Machines with libFM, in ACM Trans. Intell. Syst. Technol., 3(3), May. [2] Steffen Rendle: Learning recommender systems with adaptive regularization. WSDM 2012: 133-142