On the use of an incremental approach to learn fuzzy classification rules for big data problems

Abstract

The MapReduce paradigm is a programming model mainly thought to process big data sets. This model has recently been used in a new proposal of a linguistic fuzzy rule-based learning algorithm. One of the most important aspects of this proposal is the use of a parallel and distributed algorithm. An alternative to this parallel and distributed organization is the use of an incremental learning algorithm in a sequential schema. We propose an incremental algorithm to learn fuzzy classification rules based on this idea and we also demonstrate through the experimental study that the proposal is very competitive when it is applied to big data problems.