While the rapid development of information technology has made easy to store and access
the huge amount of data, it also brings another problem, that of how to extract potentially …

The intent of this book is to describe some recent data mining tools that have proven
effective in dealing with data sets which often involve unc-tain description or other …

This paper shows how the rule weight of each fuzzy rule can be specified in fuzzy rule-
based classification systems. First, we propose two heuristic methods for rule weight …

Many approaches have already been proposed for classification and modeling in the
literature. These approaches are usually based on mathematical mod els. Computer …

Evolutionary algorithms have been successfully used in many studies to design accurate
and interpretable fuzzy systems under the name of genetic fuzzy systems. Recently …

Different studies have proposed methods for mining fuzzy association rules from quantitative
data, where the membership functions were assumed to be known in advance. However, it …

This paper considers the automatic design of fuzzy-rule-based classification systems from
labeled data. The performance of classifiers and the interpretability of generated rules are of …

Linguistic summarization (LS) is a data mining or knowledge discovery approach to extract
patterns from databases. Many authors have used this technique to generate summaries like …

Data mining techniques can be used to discover useful patterns by exploring and analyzing
data, so, it is feasible to incorporate data mining techniques into the classification process to …

Data mining is most commonly used in attempts to induce association rules from transaction
data. Transactions in real-world applications, however, usually consist of quantitative values …