Fuzzy rule based classification systems is one of the most popular in pattern classification problems. The rules in the fuzzy models can be weighted to show the importance of generated rules where all attributes in the antecedent part of the rules have been usually weighted equally. Whereas the contributed attributes in a fuzzy model may have different influences on the decision making, a new m...

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most conventional data-mining algorithms identify the relationships among transactions using binary values and set the minimum supports and minimum confidences at numerical values. Linguistic minimum support and minimum confidence values are, however, more natural ...

A fuzzy-genetic data-mining algorithm for extracting both association rules and membership functions from quantitative transactions is shown in this paper. It used a combination of large 1-itemsets and membershipfunction suitability to evaluate the fitness values of chromosomes. The calculation for large 1itemsets could take a lot of time, especially when the database to be scanned could not to...

Construction of effective and accurate classifier is one of the challenges facing by the researchers. Many experiments have shown that Associative Classifier is significantly more accurate than the traditional classifiers. To classify the quantitative data, Fuzzy Associative Classifier was introduced and is also proved as an effective prediction model. Mining of negative association rules have ...

A methodology to compare fuzzy association rules algorithms is presented in this paper, showing that allows the epithet on equal terms. This is motivated because of this is not a soft computing area with a experimental framework as developed as others, for example: Classi cation. One reason is that the problem itself is multiobjective. Thus, the diverse approaches are evaluated in di erent ways...

Data mining is a widely used approach for the transformation of large amounts of data to useful patterns and knowledge. Fuzzy association rules mining is a data mining technique which tries to nd association rules without the e ect of sharp boundary problems when data contains continuous and categorical attributes. Grid data mining is a new concept, which allows the data mining process to be de...

If-then rules are one of the most common forms of knowledge discovered by data mining methods. The number and the length of extracted rules tend to increase with the size of a database, making the rulesets less interpretable and useful. Existing methods of extracting fuzzy rules from numerical data improve the interpretability aspect, but the dimensionality of fuzzy rulesets remains high. In th...