Data mining with a simulated annealing based fuzzy classification system

Modeling Information Quality Risk for Data Mining and Case Studies

“…In contrast, the latter does not require pre-classification of the data and can form groups that share common characteristics. To carry out these two main task types, four business data mining approaches are commonly used: clustering (Shao & Krishnamurty, 2008), classification (Mohamadi, et al, 2008), association rules (Mitra & Chaudhuri, 2006) and visualization (Compieta et. al., 2007).…”

Autonomous learning multi-model classifier of 0-Order (ALMMo-0)

“…Nowadays, classification techniques have been widely used in different fields like natural language processing [1], [2], image processing [3], [4], etc. Fuzzy logic is now often used in the classification tasks [5], [6]. There are many methods for automatically generating and learning fuzzy IF-THEN rules from data for pattern recognition problems [7]- [11].…”

Designing simulated annealing and subtractive clustering based fuzzy classifier

“…In the last few decades the development of fast microprocessors and embedded processors have enabled the design and implementation of fuzzy inference systems on real world problems such as achieving classification tasks and pattern recognition [2,3], process control [4], decision support [5,6], robotics [7], bioinformatics [8,9] and so on. A fuzzy inference system can be built by using expert knowledge heuristically.…”