In this chapter we discuss how fuzzy logic extends the envelop of the main data mining tasks: clustering, classification, regression and association rules. We begin by presenting a formulation of the data mining using fuzzy logic attributes. Then, for each task, we provide a survey of the main algorithms and a detailed description (i.e. pseudo-code) of the most popular algorithms. However this chapter will not profoundly discuss neuro-fuzzy techniques, assuming that there will be a dedicated chapter for this issue. © 2008 Springer-Verlag US.
CITATION STYLE
Rokach, L. (2008). The role of fuzzy sets in data mining. In Soft Computing for Knowledge Discovery and Data Mining (pp. 187–203). Springer US. https://doi.org/10.1007/978-0-387-69935-6_8
Mendeley helps you to discover research relevant for your work.