The image mining technique deals with the extraction of implicit knowledge and image with data relationship or other patterns not explicitly stored in the images. It is an extension of data mining to image domain. The main objective of this paper is to apply image mining in the domain such as breast mammograms to classify and detect the cancerous tissue. Mammogram image can be classified into n...

In this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. This...

A fuzzy theory refinement algorithm composed of a heuristic process of generalization, specification, addition and elimination of rules is proposed. This refinement algorithm can be applied to knowledge bases obtained from several sources (learning algorithms, experts), but its development is strongly associated with the SLAVE learning system. SLAVE was developed for working with noise-affected...

In this paper, we propose an evolutionary method to search interesting association rules. Most of the association rule mining methods give a large number of rules, and it is difficult for human beings to deal with them. We study this problem by borrowing the style of a search engine, that is, searching association rules by keywords. Whether a rule is interesting or not is decided by its relatio...

In this study we discuss the problem of mining association rules with constrained antecedents in a large database of sales transactions or clickstream records. For a user-defined set A of items, this problem asks for computing all association rules (satisfying suitable support and confidence thresholds) induced by A, where an association rule is said to be induced by A if its antecedent (i.e., ...