Advantages of using factorisation machines as a statistical modelling technique

Erika Slabber; Tanja Verster; Riaan de Jongh

doi:10.37920/sasj.2021.55.2.3

Erika Slabber Centre for BMI, North-West University, Potchefstroom, South Africa
Tanja Verster Centre for BMI, North-West University, Potchefstroom, South Africa
Riaan de Jongh Centre for BMI, North-West University, Potchefstroom, South Africa

DOI: https://doi.org/10.37920/sasj.2021.55.2.3

Keywords: Factorisation machines, Linear regression, Machine learning, Recommender systems

Abstract

Factorisation machines originated from the field of machine learning literature and have gained popularity because of the high accuracy obtained in several prediction problems, in particular in the area of recommender systems. This article will provide a motivation for the use of factorisation machines, discuss the fundamentals of factorisation machines, and provide examples of some applications and the possible gains by using factorisation machines as part of the statistician’s model-building toolkit. Data sets and existing software packages will be used to illustrate how factorisation machines may be fitted and in what context it is worth being used.