A new approach to clustering

Application of Genetic Algorithm Based Intuitionistic Fuzzy k-Mode for Clustering Categorical Data

“…Instead of assigning each object to one cluster, the fuzzy k-Modes clustering algorithm calculates a cluster membership degree value for each object to each cluster. Similar to the fuzzy k-Means [5,6,20], this is achieved by introducing the fuzziness factor in the objective function. This algorithm has found applications in bioinformatics.…”

“…From categorical data a fuzzy partition matrix is generated within the framework of the fuzzy k-Means algorithm [5,6]. Its primary concern is to bring out a method to get the fuzzy cluster modes [7,8] from the categorical entities when the simple matching dissimilarity is applied to them.…”

A systematic approach to the assessment of fuzzy association rules

“…for all potential objects x [32]. This leads us to the admissible operators problem: Which generalized conjunctions (t-norms) ⊗ and generalized implications do satisfy (11) with S + , S − , and S ± given by (10)?…”

Fuzzy Sets: History and Basic Notions

“…The notion of a fuzzy partition was first proposed by Ruspini (1969). A fuzzy partition is a family of fuzzy sets {F 1 ,…, F n } such that ∀i = 1, …, n, F i ≠ Ø, F i ≠ U, and ∀u ∈U, ∑ i = 1,…,n F i (u) = 1.…”